commo...

erans Mon, 12 Dec 2016 08:28:12 -0800

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html
 Mon Dec 12 16:27:09 2016
@@ -27,125 +27,123 @@
 <a class="jxr_linenumber" name="L19" href="#L19">19</a>  <strong 
class="jxr_keyword">import</strong> 
org.apache.commons.rng.UniformRandomProvider;
 <a class="jxr_linenumber" name="L20" href="#L20">20</a>  
 <a class="jxr_linenumber" name="L21" href="#L21">21</a>  <em 
class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L22" href="#L22">22</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;</em>
-<a class="jxr_linenumber" name="L23" href="#L23">23</a>  <em 
class="jxr_javadoccomment"> * Sampling from the &lt;a href="<a 
href="http://mathworld.wolfram.com/GammaDistribution.html"; 
target="alexandria_uri">http://mathworld.wolfram.com/GammaDistribution.html</a>"&gt;Gamma
 distribution&lt;/a&gt;.</em>
-<a class="jxr_linenumber" name="L24" href="#L24">24</a>  <em 
class="jxr_javadoccomment"> * &lt;ul&gt;</em>
-<a class="jxr_linenumber" name="L25" href="#L25">25</a>  <em 
class="jxr_javadoccomment"> *  &lt;li&gt;</em>
-<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> *   For {@code 0 &lt; shape &lt; 1}:</em>
-<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> *   &lt;blockquote&gt;</em>
-<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> *    Ahrens, J. H. and Dieter, U.,</em>
-<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> *    &lt;i&gt;Computer methods for sampling from 
gamma, beta, Poisson and binomial distributions,&lt;/i&gt;</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> *    Computing, 12, 223-246, 1974.</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> *   &lt;/blockquote&gt;</em>
-<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> *  &lt;/li&gt;</em>
-<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> *  &lt;li&gt;</em>
-<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> *  For {@code shape &gt;= 1}:</em>
-<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> *   &lt;blockquote&gt;</em>
-<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> *   Marsaglia and Tsang, &lt;i&gt;A Simple Method 
for Generating</em>
-<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> *   Gamma Variables.&lt;/i&gt; ACM Transactions on 
Mathematical Software,</em>
-<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> *   Volume 26 Issue 3, September, 2000.</em>
-<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> *   &lt;/blockquote&gt;</em>
-<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> *  &lt;/li&gt;</em>
-<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> * &lt;/ul&gt;</em>
-<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <em 
class="jxr_javadoccomment"> * &lt;/p&gt;</em>
-<a class="jxr_linenumber" name="L43" href="#L43">43</a>  <em 
class="jxr_javadoccomment"> */</em>
-<a class="jxr_linenumber" name="L44" href="#L44">44</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html">AhrensDieterMarsagliaTsangGammaSampler</a>
-<a class="jxr_linenumber" name="L45" href="#L45">45</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
-<a class="jxr_linenumber" name="L46" href="#L46">46</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousSampler.html">ContinuousSampler</a>
 {
-<a class="jxr_linenumber" name="L47" href="#L47">47</a>      <em 
class="jxr_javadoccomment">/** The shape parameter. */</em>
-<a class="jxr_linenumber" name="L48" href="#L48">48</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<strong class="jxr_keyword">double</strong> theta;
-<a class="jxr_linenumber" name="L49" href="#L49">49</a>      <em 
class="jxr_javadoccomment">/** The alpha parameter. */</em>
-<a class="jxr_linenumber" name="L50" href="#L50">50</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<strong class="jxr_keyword">double</strong> alpha;
-<a class="jxr_linenumber" name="L51" href="#L51">51</a>      <em 
class="jxr_javadoccomment">/** Gaussian sampling. */</em>
-<a class="jxr_linenumber" name="L52" href="#L52">52</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.html">BoxMullerGaussianSampler</a>
 gaussian;
-<a class="jxr_linenumber" name="L53" href="#L53">53</a>  
-<a class="jxr_linenumber" name="L54" href="#L54">54</a>      <em 
class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L55" href="#L55">55</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
-<a class="jxr_linenumber" name="L56" href="#L56">56</a>  <em 
class="jxr_javadoccomment">     * @param alpha Alpha parameter of the 
distribution.</em>
-<a class="jxr_linenumber" name="L57" href="#L57">57</a>  <em 
class="jxr_javadoccomment">     * @param theta Theta parameter of the 
distribution.</em>
-<a class="jxr_linenumber" name="L58" href="#L58">58</a>  <em 
class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L59" href="#L59">59</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html">AhrensDieterMarsagliaTsangGammaSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
-<a class="jxr_linenumber" name="L60" href="#L60">60</a>                        
                            <strong class="jxr_keyword">double</strong> alpha,
-<a class="jxr_linenumber" name="L61" href="#L61">61</a>                        
                            <strong class="jxr_keyword">double</strong> theta) {
-<a class="jxr_linenumber" name="L62" href="#L62">62</a>          <strong 
class="jxr_keyword">super</strong>(rng);
-<a class="jxr_linenumber" name="L63" href="#L63">63</a>          <strong 
class="jxr_keyword">this</strong>.alpha = alpha;
-<a class="jxr_linenumber" name="L64" href="#L64">64</a>          <strong 
class="jxr_keyword">this</strong>.theta = theta;
-<a class="jxr_linenumber" name="L65" href="#L65">65</a>          gaussian = 
<strong class="jxr_keyword">new</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.html">BoxMullerGaussianSampler</a>(rng,
 0, 1);
-<a class="jxr_linenumber" name="L66" href="#L66">66</a>      }
-<a class="jxr_linenumber" name="L67" href="#L67">67</a>  
-<a class="jxr_linenumber" name="L68" href="#L68">68</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L69" href="#L69">69</a>      @Override
-<a class="jxr_linenumber" name="L70" href="#L70">70</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">double</strong> 
sample() {
-<a class="jxr_linenumber" name="L71" href="#L71">71</a>          <strong 
class="jxr_keyword">if</strong> (theta &lt; 1) {
-<a class="jxr_linenumber" name="L72" href="#L72">72</a>              <em 
class="jxr_comment">// [1]: p. 228, Algorithm GS.</em>
-<a class="jxr_linenumber" name="L73" href="#L73">73</a>  
-<a class="jxr_linenumber" name="L74" href="#L74">74</a>              <strong 
class="jxr_keyword">while</strong> (<strong class="jxr_keyword">true</strong>) {
-<a class="jxr_linenumber" name="L75" href="#L75">75</a>                  <em 
class="jxr_comment">// Step 1:</em>
-<a class="jxr_linenumber" name="L76" href="#L76">76</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u = nextDouble();
-<a class="jxr_linenumber" name="L77" href="#L77">77</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> bGS = 1 + theta / Math.E;
-<a class="jxr_linenumber" name="L78" href="#L78">78</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> p = bGS * u;
-<a class="jxr_linenumber" name="L79" href="#L79">79</a>  
-<a class="jxr_linenumber" name="L80" href="#L80">80</a>                  
<strong class="jxr_keyword">if</strong> (p &lt;= 1) {
-<a class="jxr_linenumber" name="L81" href="#L81">81</a>                      
<em class="jxr_comment">// Step 2:</em>
-<a class="jxr_linenumber" name="L82" href="#L82">82</a>  
-<a class="jxr_linenumber" name="L83" href="#L83">83</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> x = Math.pow(p, 1 / theta);
-<a class="jxr_linenumber" name="L84" href="#L84">84</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u2 = nextDouble();
-<a class="jxr_linenumber" name="L85" href="#L85">85</a>  
-<a class="jxr_linenumber" name="L86" href="#L86">86</a>                      
<strong class="jxr_keyword">if</strong> (u2 &gt; Math.exp(-x)) {
-<a class="jxr_linenumber" name="L87" href="#L87">87</a>                        
  <em class="jxr_comment">// Reject.</em>
-<a class="jxr_linenumber" name="L88" href="#L88">88</a>                        
  <strong class="jxr_keyword">continue</strong>;
-<a class="jxr_linenumber" name="L89" href="#L89">89</a>                      } 
<strong class="jxr_keyword">else</strong> {
-<a class="jxr_linenumber" name="L90" href="#L90">90</a>                        
  <strong class="jxr_keyword">return</strong> alpha * x;
-<a class="jxr_linenumber" name="L91" href="#L91">91</a>                      }
-<a class="jxr_linenumber" name="L92" href="#L92">92</a>                  } 
<strong class="jxr_keyword">else</strong> {
-<a class="jxr_linenumber" name="L93" href="#L93">93</a>                      
<em class="jxr_comment">// Step 3:</em>
-<a class="jxr_linenumber" name="L94" href="#L94">94</a>  
-<a class="jxr_linenumber" name="L95" href="#L95">95</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> x = -1 * Math.log((bGS - p) / theta);
-<a class="jxr_linenumber" name="L96" href="#L96">96</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u2 = nextDouble();
-<a class="jxr_linenumber" name="L97" href="#L97">97</a>  
-<a class="jxr_linenumber" name="L98" href="#L98">98</a>                      
<strong class="jxr_keyword">if</strong> (u2 &gt; Math.pow(x, theta - 1)) {
-<a class="jxr_linenumber" name="L99" href="#L99">99</a>                        
  <em class="jxr_comment">// Reject.</em>
-<a class="jxr_linenumber" name="L100" href="#L100">100</a>                     
    <strong class="jxr_keyword">continue</strong>;
-<a class="jxr_linenumber" name="L101" href="#L101">101</a>                     
} <strong class="jxr_keyword">else</strong> {
-<a class="jxr_linenumber" name="L102" href="#L102">102</a>                     
    <strong class="jxr_keyword">return</strong> alpha * x;
-<a class="jxr_linenumber" name="L103" href="#L103">103</a>                     
}
-<a class="jxr_linenumber" name="L104" href="#L104">104</a>                 }
-<a class="jxr_linenumber" name="L105" href="#L105">105</a>             }
-<a class="jxr_linenumber" name="L106" href="#L106">106</a>         }
+<a class="jxr_linenumber" name="L22" href="#L22">22</a>  <em 
class="jxr_javadoccomment"> * Sampling from the &lt;a href="<a 
href="http://mathworld.wolfram.com/GammaDistribution.html"; 
target="alexandria_uri">http://mathworld.wolfram.com/GammaDistribution.html</a>"&gt;Gamma
 distribution&lt;/a&gt;.</em>
+<a class="jxr_linenumber" name="L23" href="#L23">23</a>  <em 
class="jxr_javadoccomment"> * &lt;ul&gt;</em>
+<a class="jxr_linenumber" name="L24" href="#L24">24</a>  <em 
class="jxr_javadoccomment"> *  &lt;li&gt;</em>
+<a class="jxr_linenumber" name="L25" href="#L25">25</a>  <em 
class="jxr_javadoccomment"> *   For {@code 0 &lt; shape &lt; 1}:</em>
+<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> *   &lt;blockquote&gt;</em>
+<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> *    Ahrens, J. H. and Dieter, U.,</em>
+<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> *    &lt;i&gt;Computer methods for sampling from 
gamma, beta, Poisson and binomial distributions,&lt;/i&gt;</em>
+<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> *    Computing, 12, 223-246, 1974.</em>
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> *   &lt;/blockquote&gt;</em>
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> *  &lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> *  &lt;li&gt;</em>
+<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> *  For {@code shape &gt;= 1}:</em>
+<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> *   &lt;blockquote&gt;</em>
+<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> *   Marsaglia and Tsang, &lt;i&gt;A Simple Method 
for Generating</em>
+<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> *   Gamma Variables.&lt;/i&gt; ACM Transactions on 
Mathematical Software,</em>
+<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> *   Volume 26 Issue 3, September, 2000.</em>
+<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> *   &lt;/blockquote&gt;</em>
+<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> *  &lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> * &lt;/ul&gt;</em>
+<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> */</em>
+<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html">AhrensDieterMarsagliaTsangGammaSampler</a>
+<a class="jxr_linenumber" name="L43" href="#L43">43</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
+<a class="jxr_linenumber" name="L44" href="#L44">44</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousSampler.html">ContinuousSampler</a>
 {
+<a class="jxr_linenumber" name="L45" href="#L45">45</a>      <em 
class="jxr_javadoccomment">/** The shape parameter. */</em>
+<a class="jxr_linenumber" name="L46" href="#L46">46</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<strong class="jxr_keyword">double</strong> theta;
+<a class="jxr_linenumber" name="L47" href="#L47">47</a>      <em 
class="jxr_javadoccomment">/** The alpha parameter. */</em>
+<a class="jxr_linenumber" name="L48" href="#L48">48</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<strong class="jxr_keyword">double</strong> alpha;
+<a class="jxr_linenumber" name="L49" href="#L49">49</a>      <em 
class="jxr_javadoccomment">/** Gaussian sampling. */</em>
+<a class="jxr_linenumber" name="L50" href="#L50">50</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.html">BoxMullerGaussianSampler</a>
 gaussian;
+<a class="jxr_linenumber" name="L51" href="#L51">51</a>  
+<a class="jxr_linenumber" name="L52" href="#L52">52</a>      <em 
class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L53" href="#L53">53</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
+<a class="jxr_linenumber" name="L54" href="#L54">54</a>  <em 
class="jxr_javadoccomment">     * @param alpha Alpha parameter of the 
distribution.</em>
+<a class="jxr_linenumber" name="L55" href="#L55">55</a>  <em 
class="jxr_javadoccomment">     * @param theta Theta parameter of the 
distribution.</em>
+<a class="jxr_linenumber" name="L56" href="#L56">56</a>  <em 
class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/AhrensDieterMarsagliaTsangGammaSampler.html">AhrensDieterMarsagliaTsangGammaSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
+<a class="jxr_linenumber" name="L58" href="#L58">58</a>                        
                            <strong class="jxr_keyword">double</strong> alpha,
+<a class="jxr_linenumber" name="L59" href="#L59">59</a>                        
                            <strong class="jxr_keyword">double</strong> theta) {
+<a class="jxr_linenumber" name="L60" href="#L60">60</a>          <strong 
class="jxr_keyword">super</strong>(rng);
+<a class="jxr_linenumber" name="L61" href="#L61">61</a>          <strong 
class="jxr_keyword">this</strong>.alpha = alpha;
+<a class="jxr_linenumber" name="L62" href="#L62">62</a>          <strong 
class="jxr_keyword">this</strong>.theta = theta;
+<a class="jxr_linenumber" name="L63" href="#L63">63</a>          gaussian = 
<strong class="jxr_keyword">new</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/BoxMullerGaussianSampler.html">BoxMullerGaussianSampler</a>(rng,
 0, 1);
+<a class="jxr_linenumber" name="L64" href="#L64">64</a>      }
+<a class="jxr_linenumber" name="L65" href="#L65">65</a>  
+<a class="jxr_linenumber" name="L66" href="#L66">66</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L67" href="#L67">67</a>      @Override
+<a class="jxr_linenumber" name="L68" href="#L68">68</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">double</strong> 
sample() {
+<a class="jxr_linenumber" name="L69" href="#L69">69</a>          <strong 
class="jxr_keyword">if</strong> (theta &lt; 1) {
+<a class="jxr_linenumber" name="L70" href="#L70">70</a>              <em 
class="jxr_comment">// [1]: p. 228, Algorithm GS.</em>
+<a class="jxr_linenumber" name="L71" href="#L71">71</a>  
+<a class="jxr_linenumber" name="L72" href="#L72">72</a>              <strong 
class="jxr_keyword">while</strong> (<strong class="jxr_keyword">true</strong>) {
+<a class="jxr_linenumber" name="L73" href="#L73">73</a>                  <em 
class="jxr_comment">// Step 1:</em>
+<a class="jxr_linenumber" name="L74" href="#L74">74</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u = nextDouble();
+<a class="jxr_linenumber" name="L75" href="#L75">75</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> bGS = 1 + theta / Math.E;
+<a class="jxr_linenumber" name="L76" href="#L76">76</a>                  
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> p = bGS * u;
+<a class="jxr_linenumber" name="L77" href="#L77">77</a>  
+<a class="jxr_linenumber" name="L78" href="#L78">78</a>                  
<strong class="jxr_keyword">if</strong> (p &lt;= 1) {
+<a class="jxr_linenumber" name="L79" href="#L79">79</a>                      
<em class="jxr_comment">// Step 2:</em>
+<a class="jxr_linenumber" name="L80" href="#L80">80</a>  
+<a class="jxr_linenumber" name="L81" href="#L81">81</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> x = Math.pow(p, 1 / theta);
+<a class="jxr_linenumber" name="L82" href="#L82">82</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u2 = nextDouble();
+<a class="jxr_linenumber" name="L83" href="#L83">83</a>  
+<a class="jxr_linenumber" name="L84" href="#L84">84</a>                      
<strong class="jxr_keyword">if</strong> (u2 &gt; Math.exp(-x)) {
+<a class="jxr_linenumber" name="L85" href="#L85">85</a>                        
  <em class="jxr_comment">// Reject.</em>
+<a class="jxr_linenumber" name="L86" href="#L86">86</a>                        
  <strong class="jxr_keyword">continue</strong>;
+<a class="jxr_linenumber" name="L87" href="#L87">87</a>                      } 
<strong class="jxr_keyword">else</strong> {
+<a class="jxr_linenumber" name="L88" href="#L88">88</a>                        
  <strong class="jxr_keyword">return</strong> alpha * x;
+<a class="jxr_linenumber" name="L89" href="#L89">89</a>                      }
+<a class="jxr_linenumber" name="L90" href="#L90">90</a>                  } 
<strong class="jxr_keyword">else</strong> {
+<a class="jxr_linenumber" name="L91" href="#L91">91</a>                      
<em class="jxr_comment">// Step 3:</em>
+<a class="jxr_linenumber" name="L92" href="#L92">92</a>  
+<a class="jxr_linenumber" name="L93" href="#L93">93</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> x = -1 * Math.log((bGS - p) / theta);
+<a class="jxr_linenumber" name="L94" href="#L94">94</a>                      
<strong class="jxr_keyword">final</strong> <strong 
class="jxr_keyword">double</strong> u2 = nextDouble();
+<a class="jxr_linenumber" name="L95" href="#L95">95</a>  
+<a class="jxr_linenumber" name="L96" href="#L96">96</a>                      
<strong class="jxr_keyword">if</strong> (u2 &gt; Math.pow(x, theta - 1)) {
+<a class="jxr_linenumber" name="L97" href="#L97">97</a>                        
  <em class="jxr_comment">// Reject.</em>
+<a class="jxr_linenumber" name="L98" href="#L98">98</a>                        
  <strong class="jxr_keyword">continue</strong>;
+<a class="jxr_linenumber" name="L99" href="#L99">99</a>                      } 
<strong class="jxr_keyword">else</strong> {
+<a class="jxr_linenumber" name="L100" href="#L100">100</a>                     
    <strong class="jxr_keyword">return</strong> alpha * x;
+<a class="jxr_linenumber" name="L101" href="#L101">101</a>                     
}
+<a class="jxr_linenumber" name="L102" href="#L102">102</a>                 }
+<a class="jxr_linenumber" name="L103" href="#L103">103</a>             }
+<a class="jxr_linenumber" name="L104" href="#L104">104</a>         }
+<a class="jxr_linenumber" name="L105" href="#L105">105</a> 
+<a class="jxr_linenumber" name="L106" href="#L106">106</a>         <em 
class="jxr_comment">// Now theta &gt;= 1.</em>
 <a class="jxr_linenumber" name="L107" href="#L107">107</a> 
-<a class="jxr_linenumber" name="L108" href="#L108">108</a>         <em 
class="jxr_comment">// Now theta &gt;= 1.</em>
-<a class="jxr_linenumber" name="L109" href="#L109">109</a> 
-<a class="jxr_linenumber" name="L110" href="#L110">110</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
d = theta - 0.333333333333333333;
-<a class="jxr_linenumber" name="L111" href="#L111">111</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
c = 1 / (3 * Math.sqrt(d));
-<a class="jxr_linenumber" name="L112" href="#L112">112</a> 
-<a class="jxr_linenumber" name="L113" href="#L113">113</a>         <strong 
class="jxr_keyword">while</strong> (<strong class="jxr_keyword">true</strong>) {
-<a class="jxr_linenumber" name="L114" href="#L114">114</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
x = gaussian.sample();
-<a class="jxr_linenumber" name="L115" href="#L115">115</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
v = (1 + c * x) * (1 + c * x) * (1 + c * x);
-<a class="jxr_linenumber" name="L116" href="#L116">116</a> 
-<a class="jxr_linenumber" name="L117" href="#L117">117</a>             <strong 
class="jxr_keyword">if</strong> (v &lt;= 0) {
-<a class="jxr_linenumber" name="L118" href="#L118">118</a>                 
<strong class="jxr_keyword">continue</strong>;
-<a class="jxr_linenumber" name="L119" href="#L119">119</a>             }
-<a class="jxr_linenumber" name="L120" href="#L120">120</a> 
-<a class="jxr_linenumber" name="L121" href="#L121">121</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
x2 = x * x;
-<a class="jxr_linenumber" name="L122" href="#L122">122</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
u = nextDouble();
-<a class="jxr_linenumber" name="L123" href="#L123">123</a> 
-<a class="jxr_linenumber" name="L124" href="#L124">124</a>             <em 
class="jxr_comment">// Squeeze.</em>
-<a class="jxr_linenumber" name="L125" href="#L125">125</a>             <strong 
class="jxr_keyword">if</strong> (u &lt; 1 - 0.0331 * x2 * x2) {
-<a class="jxr_linenumber" name="L126" href="#L126">126</a>                 
<strong class="jxr_keyword">return</strong> alpha * d * v;
-<a class="jxr_linenumber" name="L127" href="#L127">127</a>             }
-<a class="jxr_linenumber" name="L128" href="#L128">128</a> 
-<a class="jxr_linenumber" name="L129" href="#L129">129</a>             <strong 
class="jxr_keyword">if</strong> (Math.log(u) &lt; 0.5 * x2 + d * (1 - v + 
Math.log(v))) {
-<a class="jxr_linenumber" name="L130" href="#L130">130</a>                 
<strong class="jxr_keyword">return</strong> alpha * d * v;
-<a class="jxr_linenumber" name="L131" href="#L131">131</a>             }
-<a class="jxr_linenumber" name="L132" href="#L132">132</a>         }
-<a class="jxr_linenumber" name="L133" href="#L133">133</a>     }
-<a class="jxr_linenumber" name="L134" href="#L134">134</a> 
-<a class="jxr_linenumber" name="L135" href="#L135">135</a>     <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L136" href="#L136">136</a>     @Override
-<a class="jxr_linenumber" name="L137" href="#L137">137</a>     <strong 
class="jxr_keyword">public</strong> String toString() {
-<a class="jxr_linenumber" name="L138" href="#L138">138</a>         <strong 
class="jxr_keyword">return</strong> <span 
class="jxr_string">"Ahrens-Dieter-Marsaglia-Tsang Gamma deviate ["</span> + 
<strong class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
-<a class="jxr_linenumber" name="L139" href="#L139">139</a>     }
-<a class="jxr_linenumber" name="L140" href="#L140">140</a> }
+<a class="jxr_linenumber" name="L108" href="#L108">108</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
d = theta - 0.333333333333333333;
+<a class="jxr_linenumber" name="L109" href="#L109">109</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
c = 1 / (3 * Math.sqrt(d));
+<a class="jxr_linenumber" name="L110" href="#L110">110</a> 
+<a class="jxr_linenumber" name="L111" href="#L111">111</a>         <strong 
class="jxr_keyword">while</strong> (<strong class="jxr_keyword">true</strong>) {
+<a class="jxr_linenumber" name="L112" href="#L112">112</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
x = gaussian.sample();
+<a class="jxr_linenumber" name="L113" href="#L113">113</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
v = (1 + c * x) * (1 + c * x) * (1 + c * x);
+<a class="jxr_linenumber" name="L114" href="#L114">114</a> 
+<a class="jxr_linenumber" name="L115" href="#L115">115</a>             <strong 
class="jxr_keyword">if</strong> (v &lt;= 0) {
+<a class="jxr_linenumber" name="L116" href="#L116">116</a>                 
<strong class="jxr_keyword">continue</strong>;
+<a class="jxr_linenumber" name="L117" href="#L117">117</a>             }
+<a class="jxr_linenumber" name="L118" href="#L118">118</a> 
+<a class="jxr_linenumber" name="L119" href="#L119">119</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
x2 = x * x;
+<a class="jxr_linenumber" name="L120" href="#L120">120</a>             <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
u = nextDouble();
+<a class="jxr_linenumber" name="L121" href="#L121">121</a> 
+<a class="jxr_linenumber" name="L122" href="#L122">122</a>             <em 
class="jxr_comment">// Squeeze.</em>
+<a class="jxr_linenumber" name="L123" href="#L123">123</a>             <strong 
class="jxr_keyword">if</strong> (u &lt; 1 - 0.0331 * x2 * x2) {
+<a class="jxr_linenumber" name="L124" href="#L124">124</a>                 
<strong class="jxr_keyword">return</strong> alpha * d * v;
+<a class="jxr_linenumber" name="L125" href="#L125">125</a>             }
+<a class="jxr_linenumber" name="L126" href="#L126">126</a> 
+<a class="jxr_linenumber" name="L127" href="#L127">127</a>             <strong 
class="jxr_keyword">if</strong> (Math.log(u) &lt; 0.5 * x2 + d * (1 - v + 
Math.log(v))) {
+<a class="jxr_linenumber" name="L128" href="#L128">128</a>                 
<strong class="jxr_keyword">return</strong> alpha * d * v;
+<a class="jxr_linenumber" name="L129" href="#L129">129</a>             }
+<a class="jxr_linenumber" name="L130" href="#L130">130</a>         }
+<a class="jxr_linenumber" name="L131" href="#L131">131</a>     }
+<a class="jxr_linenumber" name="L132" href="#L132">132</a> 
+<a class="jxr_linenumber" name="L133" href="#L133">133</a>     <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L134" href="#L134">134</a>     @Override
+<a class="jxr_linenumber" name="L135" href="#L135">135</a>     <strong 
class="jxr_keyword">public</strong> String toString() {
+<a class="jxr_linenumber" name="L136" href="#L136">136</a>         <strong 
class="jxr_keyword">return</strong> <span 
class="jxr_string">"Ahrens-Dieter-Marsaglia-Tsang Gamma deviate ["</span> + 
<strong class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
+<a class="jxr_linenumber" name="L137" href="#L137">137</a>     }
+<a class="jxr_linenumber" name="L138" href="#L138">138</a> }
 </pre>
 <hr/>
 <div id="footer">Copyright &#169; 2016 <a href="https://www.apache.org/";>The 
Apache Software Foundation</a>. All rights reserved.</div>


Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html
 Mon Dec 12 16:27:09 2016
@@ -35,8 +35,8 @@
 <a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment">     * For a random variable {@code X} distributed 
according to this distribution,</em>
 <a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment">     * the returned value is</em>
 <a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment">     * &lt;ul&gt;</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{R}} P(X 
\le x) \ge p \) for \( 0 &lt; p \le 1 \)&lt;/li&gt;</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{R}} P(X 
\le x) &gt; 0   \) for \( p = 0 \)&lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{R}} P(X 
\le x) \ge p \) for \( 0 \lt p \le 1 \)&lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{R}} P(X 
\le x) \gt 0 \) for \( p = 0 \)&lt;/li&gt;</em>
 <a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment">     * &lt;/ul&gt;</em>
 <a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment">     *</em>
 <a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment">     * @param p Cumulative probability.</em>

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html
 Mon Dec 12 16:27:09 2016
@@ -35,8 +35,8 @@
 <a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment">     * For a random variable {@code X} distributed 
according to this distribution,</em>
 <a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment">     * the returned value is</em>
 <a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment">     * &lt;ul&gt;</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{Z}} P(X 
\le x) \ge p \) for \( 0 &lt; p \le 1 \)&lt;/li&gt;</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{Z}} P(X 
\le x) &gt; 0   \) for \( p = 0 \)&lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{Z}} P(X 
\le x) \ge p \) for \( 0 \lt p \le 1 \)&lt;/li&gt;</em>
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment">     *  &lt;li&gt;\( \inf_{x \in \mathcal{Z}} P(X 
\le x) \gt 0 \) for \( p = 0 \)&lt;/li&gt;</em>
 <a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment">     * &lt;/ul&gt;</em>
 <a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment">     *</em>
 <a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment">     * @param p Cumulative probability.</em>

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InternalGamma.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InternalGamma.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InternalGamma.html
 Mon Dec 12 16:27:09 2016
@@ -121,7 +121,7 @@
 <a class="jxr_linenumber" name="L113" href="#L113">113</a> 
 <a class="jxr_linenumber" name="L114" href="#L114">114</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
sum = lanczos(x);
 <a class="jxr_linenumber" name="L115" href="#L115">115</a>         <strong 
class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> 
tmp = x + LANCZOS_G + 0.5;
-<a class="jxr_linenumber" name="L116" href="#L116">116</a>         <strong 
class="jxr_keyword">return</strong> ((x + 0.5) * Math.log(tmp)) - tmp +  
HALF_LOG_2_PI + Math.log(sum / x);
+<a class="jxr_linenumber" name="L116" href="#L116">116</a>         <strong 
class="jxr_keyword">return</strong> (x + 0.5) * Math.log(tmp) - tmp +  
HALF_LOG_2_PI + Math.log(sum / x);
 <a class="jxr_linenumber" name="L117" href="#L117">117</a>     }
 <a class="jxr_linenumber" name="L118" href="#L118">118</a> 
 <a class="jxr_linenumber" name="L119" href="#L119">119</a>     <em 
class="jxr_javadoccomment">/**</em>

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html
 Mon Dec 12 16:27:09 2016
@@ -31,64 +31,62 @@
 <a class="jxr_linenumber" name="L23" href="#L23">23</a>  <em 
class="jxr_javadoccomment"> * &lt;a 
href="https://en.wikipedia.org/wiki/Inverse_transform_sampling"&gt;</em>
 <a class="jxr_linenumber" name="L24" href="#L24">24</a>  <em 
class="jxr_javadoccomment"> * inversion method&lt;/a&gt;.</em>
 <a class="jxr_linenumber" name="L25" href="#L25">25</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;</em>
-<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> * It can be used to sample any distribution that 
provides access to its</em>
-<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> * &lt;em&gt;inverse cumulative probabilty 
function&lt;/em&gt;.</em>
-<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> * &lt;/p&gt;</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;Example:&lt;/p&gt;</em>
-<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> * &lt;pre&gt;&lt;source&gt;</em>
-<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.RealDistribution;</em>
-<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.ChiSquaredDistribution;</em>
-<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.simple.RandomSource;</em>
-<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.ContinuousSampler;</em>
-<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler;</em>
-<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction;</em>
-<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> * // Distribution to sample.</em>
-<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <em 
class="jxr_javadoccomment"> * final RealDistribution dist = new 
ChiSquaredDistribution(9);</em>
-<a class="jxr_linenumber" name="L43" href="#L43">43</a>  <em 
class="jxr_javadoccomment"> * // Create the sampler.</em>
-<a class="jxr_linenumber" name="L44" href="#L44">44</a>  <em 
class="jxr_javadoccomment"> * final ContinuousSampler chiSquareSampler =</em>
-<a class="jxr_linenumber" name="L45" href="#L45">45</a>  <em 
class="jxr_javadoccomment"> *     new 
InverseTransformContinuousSampler(RandomSource.create(RandomSource.MT),</em>
-<a class="jxr_linenumber" name="L46" href="#L46">46</a>  <em 
class="jxr_javadoccomment"> *                                        new 
ContinuousInverseCumulativeProbabilityFunction() {</em>
-<a class="jxr_linenumber" name="L47" href="#L47">47</a>  <em 
class="jxr_javadoccomment"> *                                            public 
double inverseCumulativeProbability(double p) {</em>
-<a class="jxr_linenumber" name="L48" href="#L48">48</a>  <em 
class="jxr_javadoccomment"> *                                                
return dist.inverseCumulativeProbability(p);</em>
-<a class="jxr_linenumber" name="L49" href="#L49">49</a>  <em 
class="jxr_javadoccomment"> *                                            }</em>
-<a class="jxr_linenumber" name="L50" href="#L50">50</a>  <em 
class="jxr_javadoccomment"> *                                        });</em>
-<a class="jxr_linenumber" name="L51" href="#L51">51</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L52" href="#L52">52</a>  <em 
class="jxr_javadoccomment"> * // Generate random deviate.</em>
-<a class="jxr_linenumber" name="L53" href="#L53">53</a>  <em 
class="jxr_javadoccomment"> * double random = chiSquareSampler.sample();</em>
-<a class="jxr_linenumber" name="L54" href="#L54">54</a>  <em 
class="jxr_javadoccomment"> * &lt;/source&gt;&lt;/pre&gt;</em>
-<a class="jxr_linenumber" name="L55" href="#L55">55</a>  <em 
class="jxr_javadoccomment"> */</em>
-<a class="jxr_linenumber" name="L56" href="#L56">56</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html">InverseTransformContinuousSampler</a>
-<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
-<a class="jxr_linenumber" name="L58" href="#L58">58</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousSampler.html">ContinuousSampler</a>
 {
-<a class="jxr_linenumber" name="L59" href="#L59">59</a>      <em 
class="jxr_javadoccomment">/** Inverse cumulative probability function. */</em>
-<a class="jxr_linenumber" name="L60" href="#L60">60</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html">ContinuousInverseCumulativeProbabilityFunction</a>
 function;
-<a class="jxr_linenumber" name="L61" href="#L61">61</a>  
-<a class="jxr_linenumber" name="L62" href="#L62">62</a>      <em 
class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L63" href="#L63">63</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
-<a class="jxr_linenumber" name="L64" href="#L64">64</a>  <em 
class="jxr_javadoccomment">     * @param function Inverse cumulative 
probability function.</em>
-<a class="jxr_linenumber" name="L65" href="#L65">65</a>  <em 
class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L66" href="#L66">66</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html">InverseTransformContinuousSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
-<a class="jxr_linenumber" name="L67" href="#L67">67</a>                        
                       <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html">ContinuousInverseCumulativeProbabilityFunction</a>
 function) {
-<a class="jxr_linenumber" name="L68" href="#L68">68</a>          <strong 
class="jxr_keyword">super</strong>(rng);
-<a class="jxr_linenumber" name="L69" href="#L69">69</a>          <strong 
class="jxr_keyword">this</strong>.function = function;
-<a class="jxr_linenumber" name="L70" href="#L70">70</a>      }
-<a class="jxr_linenumber" name="L71" href="#L71">71</a>  
-<a class="jxr_linenumber" name="L72" href="#L72">72</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L73" href="#L73">73</a>      @Override
-<a class="jxr_linenumber" name="L74" href="#L74">74</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">double</strong> 
sample() {
-<a class="jxr_linenumber" name="L75" href="#L75">75</a>          <strong 
class="jxr_keyword">return</strong> 
function.inverseCumulativeProbability(nextDouble());
-<a class="jxr_linenumber" name="L76" href="#L76">76</a>      }
-<a class="jxr_linenumber" name="L77" href="#L77">77</a>  
-<a class="jxr_linenumber" name="L78" href="#L78">78</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L79" href="#L79">79</a>      @Override
-<a class="jxr_linenumber" name="L80" href="#L80">80</a>      <strong 
class="jxr_keyword">public</strong> String toString() {
-<a class="jxr_linenumber" name="L81" href="#L81">81</a>          <strong 
class="jxr_keyword">return</strong> function.toString() + <span 
class="jxr_string">" (inverse method) ["</span> + <strong 
class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
-<a class="jxr_linenumber" name="L82" href="#L82">82</a>      }
-<a class="jxr_linenumber" name="L83" href="#L83">83</a>  }
+<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> * It can be used to sample any distribution that 
provides access to its</em>
+<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> * &lt;em&gt;inverse cumulative probabilty 
function&lt;/em&gt;.</em>
+<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;Example:&lt;/p&gt;</em>
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> * &lt;pre&gt;&lt;code&gt;</em>
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.RealDistribution;</em>
+<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.ChiSquaredDistribution;</em>
+<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.simple.RandomSource;</em>
+<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.ContinuousSampler;</em>
+<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.InverseTransformContinuousSampler;</em>
+<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.ContinuousInverseCumulativeProbabilityFunction;</em>
+<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> * // Distribution to sample.</em>
+<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> * final RealDistribution dist = new 
ChiSquaredDistribution(9);</em>
+<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> * // Create the sampler.</em>
+<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <em 
class="jxr_javadoccomment"> * final ContinuousSampler chiSquareSampler =</em>
+<a class="jxr_linenumber" name="L43" href="#L43">43</a>  <em 
class="jxr_javadoccomment"> *     new 
InverseTransformContinuousSampler(RandomSource.create(RandomSource.MT),</em>
+<a class="jxr_linenumber" name="L44" href="#L44">44</a>  <em 
class="jxr_javadoccomment"> *                                           new 
ContinuousInverseCumulativeProbabilityFunction() {</em>
+<a class="jxr_linenumber" name="L45" href="#L45">45</a>  <em 
class="jxr_javadoccomment"> *                                               
public double inverseCumulativeProbability(double p) {</em>
+<a class="jxr_linenumber" name="L46" href="#L46">46</a>  <em 
class="jxr_javadoccomment"> *                                                   
return dist.inverseCumulativeProbability(p);</em>
+<a class="jxr_linenumber" name="L47" href="#L47">47</a>  <em 
class="jxr_javadoccomment"> *                                               
}</em>
+<a class="jxr_linenumber" name="L48" href="#L48">48</a>  <em 
class="jxr_javadoccomment"> *                                           });</em>
+<a class="jxr_linenumber" name="L49" href="#L49">49</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L50" href="#L50">50</a>  <em 
class="jxr_javadoccomment"> * // Generate random deviate.</em>
+<a class="jxr_linenumber" name="L51" href="#L51">51</a>  <em 
class="jxr_javadoccomment"> * double random = chiSquareSampler.sample();</em>
+<a class="jxr_linenumber" name="L52" href="#L52">52</a>  <em 
class="jxr_javadoccomment"> * &lt;/code&gt;&lt;/pre&gt;</em>
+<a class="jxr_linenumber" name="L53" href="#L53">53</a>  <em 
class="jxr_javadoccomment"> */</em>
+<a class="jxr_linenumber" name="L54" href="#L54">54</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html">InverseTransformContinuousSampler</a>
+<a class="jxr_linenumber" name="L55" href="#L55">55</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
+<a class="jxr_linenumber" name="L56" href="#L56">56</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousSampler.html">ContinuousSampler</a>
 {
+<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <em 
class="jxr_javadoccomment">/** Inverse cumulative probability function. */</em>
+<a class="jxr_linenumber" name="L58" href="#L58">58</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html">ContinuousInverseCumulativeProbabilityFunction</a>
 function;
+<a class="jxr_linenumber" name="L59" href="#L59">59</a>  
+<a class="jxr_linenumber" name="L60" href="#L60">60</a>      <em 
class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L61" href="#L61">61</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
+<a class="jxr_linenumber" name="L62" href="#L62">62</a>  <em 
class="jxr_javadoccomment">     * @param function Inverse cumulative 
probability function.</em>
+<a class="jxr_linenumber" name="L63" href="#L63">63</a>  <em 
class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L64" href="#L64">64</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformContinuousSampler.html">InverseTransformContinuousSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
+<a class="jxr_linenumber" name="L65" href="#L65">65</a>                        
                       <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/ContinuousInverseCumulativeProbabilityFunction.html">ContinuousInverseCumulativeProbabilityFunction</a>
 function) {
+<a class="jxr_linenumber" name="L66" href="#L66">66</a>          <strong 
class="jxr_keyword">super</strong>(rng);
+<a class="jxr_linenumber" name="L67" href="#L67">67</a>          <strong 
class="jxr_keyword">this</strong>.function = function;
+<a class="jxr_linenumber" name="L68" href="#L68">68</a>      }
+<a class="jxr_linenumber" name="L69" href="#L69">69</a>  
+<a class="jxr_linenumber" name="L70" href="#L70">70</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L71" href="#L71">71</a>      @Override
+<a class="jxr_linenumber" name="L72" href="#L72">72</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">double</strong> 
sample() {
+<a class="jxr_linenumber" name="L73" href="#L73">73</a>          <strong 
class="jxr_keyword">return</strong> 
function.inverseCumulativeProbability(nextDouble());
+<a class="jxr_linenumber" name="L74" href="#L74">74</a>      }
+<a class="jxr_linenumber" name="L75" href="#L75">75</a>  
+<a class="jxr_linenumber" name="L76" href="#L76">76</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L77" href="#L77">77</a>      @Override
+<a class="jxr_linenumber" name="L78" href="#L78">78</a>      <strong 
class="jxr_keyword">public</strong> String toString() {
+<a class="jxr_linenumber" name="L79" href="#L79">79</a>          <strong 
class="jxr_keyword">return</strong> function.toString() + <span 
class="jxr_string">" (inverse method) ["</span> + <strong 
class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
+<a class="jxr_linenumber" name="L80" href="#L80">80</a>      }
+<a class="jxr_linenumber" name="L81" href="#L81">81</a>  }
 </pre>
 <hr/>
 <div id="footer">Copyright &#169; 2016 <a href="https://www.apache.org/";>The 
Apache Software Foundation</a>. All rights reserved.</div>

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html
 Mon Dec 12 16:27:09 2016
@@ -31,64 +31,62 @@
 <a class="jxr_linenumber" name="L23" href="#L23">23</a>  <em 
class="jxr_javadoccomment"> * &lt;a 
href="https://en.wikipedia.org/wiki/Inverse_transform_sampling"&gt;</em>
 <a class="jxr_linenumber" name="L24" href="#L24">24</a>  <em 
class="jxr_javadoccomment"> * inversion method&lt;/a&gt;.</em>
 <a class="jxr_linenumber" name="L25" href="#L25">25</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;</em>
-<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> * It can be used to sample any distribution that 
provides access to its</em>
-<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> * &lt;em&gt;inverse cumulative probabilty 
function&lt;/em&gt;.</em>
-<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> * &lt;/p&gt;</em>
-<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;Example:&lt;/p&gt;</em>
-<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> * &lt;pre&gt;&lt;source&gt;</em>
-<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.IntegerDistribution;</em>
-<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.BinomialDistribution;</em>
-<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.simple.RandomSource;</em>
-<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.DiscreteSampler;</em>
-<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler;</em>
-<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.DiscreteInverseCumulativeProbabilityFunction;</em>
-<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> * // Distribution to sample.</em>
-<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <em 
class="jxr_javadoccomment"> * final IntegerDistribution dist = new 
BinomialDistribution(11, 0.56);</em>
-<a class="jxr_linenumber" name="L43" href="#L43">43</a>  <em 
class="jxr_javadoccomment"> * // Create the sampler.</em>
-<a class="jxr_linenumber" name="L44" href="#L44">44</a>  <em 
class="jxr_javadoccomment"> * final DiscreteSampler binomialSampler =</em>
-<a class="jxr_linenumber" name="L45" href="#L45">45</a>  <em 
class="jxr_javadoccomment"> *     new 
InverseTransformDiscreteSampler(RandomSource.create(RandomSource.MT),</em>
-<a class="jxr_linenumber" name="L46" href="#L46">46</a>  <em 
class="jxr_javadoccomment"> *                                      new 
DiscreteInverseCumulativeProbabilityFunction() {</em>
-<a class="jxr_linenumber" name="L47" href="#L47">47</a>  <em 
class="jxr_javadoccomment"> *                                          public 
int inverseCumulativeProbability(double p) {</em>
-<a class="jxr_linenumber" name="L48" href="#L48">48</a>  <em 
class="jxr_javadoccomment"> *                                              
return dist.inverseCumulativeProbability(p);</em>
-<a class="jxr_linenumber" name="L49" href="#L49">49</a>  <em 
class="jxr_javadoccomment"> *                                          }</em>
-<a class="jxr_linenumber" name="L50" href="#L50">50</a>  <em 
class="jxr_javadoccomment"> *                                      });</em>
-<a class="jxr_linenumber" name="L51" href="#L51">51</a>  <em 
class="jxr_javadoccomment"> *</em>
-<a class="jxr_linenumber" name="L52" href="#L52">52</a>  <em 
class="jxr_javadoccomment"> * // Generate random deviate.</em>
-<a class="jxr_linenumber" name="L53" href="#L53">53</a>  <em 
class="jxr_javadoccomment"> * int random = binomialSampler.sample();</em>
-<a class="jxr_linenumber" name="L54" href="#L54">54</a>  <em 
class="jxr_javadoccomment"> * &lt;/source&gt;&lt;/pre&gt;</em>
-<a class="jxr_linenumber" name="L55" href="#L55">55</a>  <em 
class="jxr_javadoccomment"> */</em>
-<a class="jxr_linenumber" name="L56" href="#L56">56</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html">InverseTransformDiscreteSampler</a>
-<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
-<a class="jxr_linenumber" name="L58" href="#L58">58</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteSampler.html">DiscreteSampler</a>
 {
-<a class="jxr_linenumber" name="L59" href="#L59">59</a>      <em 
class="jxr_javadoccomment">/** Inverse cumulative probability function. */</em>
-<a class="jxr_linenumber" name="L60" href="#L60">60</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html">DiscreteInverseCumulativeProbabilityFunction</a>
 function;
-<a class="jxr_linenumber" name="L61" href="#L61">61</a>  
-<a class="jxr_linenumber" name="L62" href="#L62">62</a>      <em 
class="jxr_javadoccomment">/**</em>
-<a class="jxr_linenumber" name="L63" href="#L63">63</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
-<a class="jxr_linenumber" name="L64" href="#L64">64</a>  <em 
class="jxr_javadoccomment">     * @param function Inverse cumulative 
probability function.</em>
-<a class="jxr_linenumber" name="L65" href="#L65">65</a>  <em 
class="jxr_javadoccomment">     */</em>
-<a class="jxr_linenumber" name="L66" href="#L66">66</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html">InverseTransformDiscreteSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
-<a class="jxr_linenumber" name="L67" href="#L67">67</a>                        
                     <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html">DiscreteInverseCumulativeProbabilityFunction</a>
 function) {
-<a class="jxr_linenumber" name="L68" href="#L68">68</a>          <strong 
class="jxr_keyword">super</strong>(rng);
-<a class="jxr_linenumber" name="L69" href="#L69">69</a>          <strong 
class="jxr_keyword">this</strong>.function = function;
-<a class="jxr_linenumber" name="L70" href="#L70">70</a>      }
-<a class="jxr_linenumber" name="L71" href="#L71">71</a>  
-<a class="jxr_linenumber" name="L72" href="#L72">72</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L73" href="#L73">73</a>      @Override
-<a class="jxr_linenumber" name="L74" href="#L74">74</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">int</strong> 
sample() {
-<a class="jxr_linenumber" name="L75" href="#L75">75</a>          <strong 
class="jxr_keyword">return</strong> 
function.inverseCumulativeProbability(nextDouble());
-<a class="jxr_linenumber" name="L76" href="#L76">76</a>      }
-<a class="jxr_linenumber" name="L77" href="#L77">77</a>  
-<a class="jxr_linenumber" name="L78" href="#L78">78</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
-<a class="jxr_linenumber" name="L79" href="#L79">79</a>      @Override
-<a class="jxr_linenumber" name="L80" href="#L80">80</a>      <strong 
class="jxr_keyword">public</strong> String toString() {
-<a class="jxr_linenumber" name="L81" href="#L81">81</a>          <strong 
class="jxr_keyword">return</strong> function.toString() + <span 
class="jxr_string">" (inverse method) ["</span> + <strong 
class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
-<a class="jxr_linenumber" name="L82" href="#L82">82</a>      }
-<a class="jxr_linenumber" name="L83" href="#L83">83</a>  }
+<a class="jxr_linenumber" name="L26" href="#L26">26</a>  <em 
class="jxr_javadoccomment"> * It can be used to sample any distribution that 
provides access to its</em>
+<a class="jxr_linenumber" name="L27" href="#L27">27</a>  <em 
class="jxr_javadoccomment"> * &lt;em&gt;inverse cumulative probabilty 
function&lt;/em&gt;.</em>
+<a class="jxr_linenumber" name="L28" href="#L28">28</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L29" href="#L29">29</a>  <em 
class="jxr_javadoccomment"> * &lt;p&gt;Example:&lt;/p&gt;</em>
+<a class="jxr_linenumber" name="L30" href="#L30">30</a>  <em 
class="jxr_javadoccomment"> * &lt;pre&gt;&lt;code&gt;</em>
+<a class="jxr_linenumber" name="L31" href="#L31">31</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.IntegerDistribution;</em>
+<a class="jxr_linenumber" name="L32" href="#L32">32</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.math3.distribution.BinomialDistribution;</em>
+<a class="jxr_linenumber" name="L33" href="#L33">33</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L34" href="#L34">34</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.simple.RandomSource;</em>
+<a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.DiscreteSampler;</em>
+<a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.InverseTransformDiscreteSampler;</em>
+<a class="jxr_linenumber" name="L37" href="#L37">37</a>  <em 
class="jxr_javadoccomment"> * import 
org.apache.commons.rng.sampling.distribution.DiscreteInverseCumulativeProbabilityFunction;</em>
+<a class="jxr_linenumber" name="L38" href="#L38">38</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L39" href="#L39">39</a>  <em 
class="jxr_javadoccomment"> * // Distribution to sample.</em>
+<a class="jxr_linenumber" name="L40" href="#L40">40</a>  <em 
class="jxr_javadoccomment"> * final IntegerDistribution dist = new 
BinomialDistribution(11, 0.56);</em>
+<a class="jxr_linenumber" name="L41" href="#L41">41</a>  <em 
class="jxr_javadoccomment"> * // Create the sampler.</em>
+<a class="jxr_linenumber" name="L42" href="#L42">42</a>  <em 
class="jxr_javadoccomment"> * final DiscreteSampler binomialSampler =</em>
+<a class="jxr_linenumber" name="L43" href="#L43">43</a>  <em 
class="jxr_javadoccomment"> *     new 
InverseTransformDiscreteSampler(RandomSource.create(RandomSource.MT),</em>
+<a class="jxr_linenumber" name="L44" href="#L44">44</a>  <em 
class="jxr_javadoccomment"> *                                         new 
DiscreteInverseCumulativeProbabilityFunction() {</em>
+<a class="jxr_linenumber" name="L45" href="#L45">45</a>  <em 
class="jxr_javadoccomment"> *                                             
public int inverseCumulativeProbability(double p) {</em>
+<a class="jxr_linenumber" name="L46" href="#L46">46</a>  <em 
class="jxr_javadoccomment"> *                                                 
return dist.inverseCumulativeProbability(p);</em>
+<a class="jxr_linenumber" name="L47" href="#L47">47</a>  <em 
class="jxr_javadoccomment"> *                                             }</em>
+<a class="jxr_linenumber" name="L48" href="#L48">48</a>  <em 
class="jxr_javadoccomment"> *                                         });</em>
+<a class="jxr_linenumber" name="L49" href="#L49">49</a>  <em 
class="jxr_javadoccomment"> *</em>
+<a class="jxr_linenumber" name="L50" href="#L50">50</a>  <em 
class="jxr_javadoccomment"> * // Generate random deviate.</em>
+<a class="jxr_linenumber" name="L51" href="#L51">51</a>  <em 
class="jxr_javadoccomment"> * int random = binomialSampler.sample();</em>
+<a class="jxr_linenumber" name="L52" href="#L52">52</a>  <em 
class="jxr_javadoccomment"> * &lt;/code&gt;&lt;/pre&gt;</em>
+<a class="jxr_linenumber" name="L53" href="#L53">53</a>  <em 
class="jxr_javadoccomment"> */</em>
+<a class="jxr_linenumber" name="L54" href="#L54">54</a>  <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">class</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html">InverseTransformDiscreteSampler</a>
+<a class="jxr_linenumber" name="L55" href="#L55">55</a>      <strong 
class="jxr_keyword">extends</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/SamplerBase.html">SamplerBase</a>
+<a class="jxr_linenumber" name="L56" href="#L56">56</a>      <strong 
class="jxr_keyword">implements</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteSampler.html">DiscreteSampler</a>
 {
+<a class="jxr_linenumber" name="L57" href="#L57">57</a>      <em 
class="jxr_javadoccomment">/** Inverse cumulative probability function. */</em>
+<a class="jxr_linenumber" name="L58" href="#L58">58</a>      <strong 
class="jxr_keyword">private</strong> <strong class="jxr_keyword">final</strong> 
<a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html">DiscreteInverseCumulativeProbabilityFunction</a>
 function;
+<a class="jxr_linenumber" name="L59" href="#L59">59</a>  
+<a class="jxr_linenumber" name="L60" href="#L60">60</a>      <em 
class="jxr_javadoccomment">/**</em>
+<a class="jxr_linenumber" name="L61" href="#L61">61</a>  <em 
class="jxr_javadoccomment">     * @param rng Generator of uniformly distributed 
random numbers.</em>
+<a class="jxr_linenumber" name="L62" href="#L62">62</a>  <em 
class="jxr_javadoccomment">     * @param function Inverse cumulative 
probability function.</em>
+<a class="jxr_linenumber" name="L63" href="#L63">63</a>  <em 
class="jxr_javadoccomment">     */</em>
+<a class="jxr_linenumber" name="L64" href="#L64">64</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformDiscreteSampler.html">InverseTransformDiscreteSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
+<a class="jxr_linenumber" name="L65" href="#L65">65</a>                        
                     <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/DiscreteInverseCumulativeProbabilityFunction.html">DiscreteInverseCumulativeProbabilityFunction</a>
 function) {
+<a class="jxr_linenumber" name="L66" href="#L66">66</a>          <strong 
class="jxr_keyword">super</strong>(rng);
+<a class="jxr_linenumber" name="L67" href="#L67">67</a>          <strong 
class="jxr_keyword">this</strong>.function = function;
+<a class="jxr_linenumber" name="L68" href="#L68">68</a>      }
+<a class="jxr_linenumber" name="L69" href="#L69">69</a>  
+<a class="jxr_linenumber" name="L70" href="#L70">70</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L71" href="#L71">71</a>      @Override
+<a class="jxr_linenumber" name="L72" href="#L72">72</a>      <strong 
class="jxr_keyword">public</strong> <strong class="jxr_keyword">int</strong> 
sample() {
+<a class="jxr_linenumber" name="L73" href="#L73">73</a>          <strong 
class="jxr_keyword">return</strong> 
function.inverseCumulativeProbability(nextDouble());
+<a class="jxr_linenumber" name="L74" href="#L74">74</a>      }
+<a class="jxr_linenumber" name="L75" href="#L75">75</a>  
+<a class="jxr_linenumber" name="L76" href="#L76">76</a>      <em 
class="jxr_javadoccomment">/** {@inheritDoc} */</em>
+<a class="jxr_linenumber" name="L77" href="#L77">77</a>      @Override
+<a class="jxr_linenumber" name="L78" href="#L78">78</a>      <strong 
class="jxr_keyword">public</strong> String toString() {
+<a class="jxr_linenumber" name="L79" href="#L79">79</a>          <strong 
class="jxr_keyword">return</strong> function.toString() + <span 
class="jxr_string">" (inverse method) ["</span> + <strong 
class="jxr_keyword">super</strong>.toString() + <span 
class="jxr_string">"]"</span>;
+<a class="jxr_linenumber" name="L80" href="#L80">80</a>      }
+<a class="jxr_linenumber" name="L81" href="#L81">81</a>  }
 </pre>
 <hr/>
 <div id="footer">Copyright &#169; 2016 <a href="https://www.apache.org/";>The 
Apache Software Foundation</a>. All rights reserved.</div>

Modified: 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.html
==============================================================================
--- 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.html
 (original)
+++ 
websites/production/commons/content/proper/commons-rng/xref/org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.html
 Mon Dec 12 16:27:09 2016
@@ -43,8 +43,8 @@
 <a class="jxr_linenumber" name="L35" href="#L35">35</a>  <em 
class="jxr_javadoccomment">     * @param shape Shape of the distribution.</em>
 <a class="jxr_linenumber" name="L36" href="#L36">36</a>  <em 
class="jxr_javadoccomment">     */</em>
 <a class="jxr_linenumber" name="L37" href="#L37">37</a>      <strong 
class="jxr_keyword">public</strong> <a 
href="../../../../../../org/apache/commons/rng/sampling/distribution/InverseTransformParetoSampler.html">InverseTransformParetoSampler</a>(<a
 
href="../../../../../../org/apache/commons/rng/UniformRandomProvider.html">UniformRandomProvider</a>
 rng,
-<a class="jxr_linenumber" name="L38" href="#L38">38</a>                        
                <strong class="jxr_keyword">double</strong> scale,
-<a class="jxr_linenumber" name="L39" href="#L39">39</a>                        
                <strong class="jxr_keyword">double</strong> shape) {
+<a class="jxr_linenumber" name="L38" href="#L38">38</a>                        
                   <strong class="jxr_keyword">double</strong> scale,
+<a class="jxr_linenumber" name="L39" href="#L39">39</a>                        
                   <strong class="jxr_keyword">double</strong> shape) {
 <a class="jxr_linenumber" name="L40" href="#L40">40</a>          <strong 
class="jxr_keyword">super</strong>(rng);
 <a class="jxr_linenumber" name="L41" href="#L41">41</a>          <strong 
class="jxr_keyword">this</strong>.scale = scale;
 <a class="jxr_linenumber" name="L42" href="#L42">42</a>          <strong 
class="jxr_keyword">this</strong>.shape = shape;

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