Added: dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NakagamiDistributionTest.html ============================================================================== --- dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NakagamiDistributionTest.html (added) +++ dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NakagamiDistributionTest.html Thu Dec 1 16:47:12 2022 @@ -0,0 +1,186 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd";> +<html xmlns="http://www.w3.org/1999/xhtml"; xml:lang="en" lang="en"> +<head><meta http-equiv="content-type" content="text/html; charset=UTF-8" /> +<title>NakagamiDistributionTest xref</title> +<link type="text/css" rel="stylesheet" href="../../../../../stylesheet.css" /> +</head> +<body> +<div id="overview"><a href="../../../../../../testapidocs/org/apache/commons/statistics/distribution/NakagamiDistributionTest.html">View Javadoc</a></div><pre> +<a class="jxr_linenumber" name="L1" href="#L1">1</a> <em class="jxr_comment">/*</em> +<a class="jxr_linenumber" name="L2" href="#L2">2</a> <em class="jxr_comment"> * Licensed to the Apache Software Foundation (ASF) under one or more</em> +<a class="jxr_linenumber" name="L3" href="#L3">3</a> <em class="jxr_comment"> * contributor license agreements. See the NOTICE file distributed with</em> +<a class="jxr_linenumber" name="L4" href="#L4">4</a> <em class="jxr_comment"> * this work for additional information regarding copyright ownership.</em> +<a class="jxr_linenumber" name="L5" href="#L5">5</a> <em class="jxr_comment"> * The ASF licenses this file to You under the Apache License, Version 2.0</em> +<a class="jxr_linenumber" name="L6" href="#L6">6</a> <em class="jxr_comment"> * (the "License"); you may not use this file except in compliance with</em> +<a class="jxr_linenumber" name="L7" href="#L7">7</a> <em class="jxr_comment"> * the License. You may obtain a copy of the License at</em> +<a class="jxr_linenumber" name="L8" href="#L8">8</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L9" href="#L9">9</a> <em class="jxr_comment"> * <a href="http://www.apache.org/licenses/LICENSE-2.0"; target="alexandria_uri">http://www.apache.org/licenses/LICENSE-2.0</a></em> +<a class="jxr_linenumber" name="L10" href="#L10">10</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L11" href="#L11">11</a> <em class="jxr_comment"> * Unless required by applicable law or agreed to in writing, software</em> +<a class="jxr_linenumber" name="L12" href="#L12">12</a> <em class="jxr_comment"> * distributed under the License is distributed on an "AS IS" BASIS,</em> +<a class="jxr_linenumber" name="L13" href="#L13">13</a> <em class="jxr_comment"> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</em> +<a class="jxr_linenumber" name="L14" href="#L14">14</a> <em class="jxr_comment"> * See the License for the specific language governing permissions and</em> +<a class="jxr_linenumber" name="L15" href="#L15">15</a> <em class="jxr_comment"> * limitations under the License.</em> +<a class="jxr_linenumber" name="L16" href="#L16">16</a> <em class="jxr_comment"> */</em> +<a class="jxr_linenumber" name="L17" href="#L17">17</a> <strong class="jxr_keyword">package</strong> org.apache.commons.statistics.distribution; +<a class="jxr_linenumber" name="L18" href="#L18">18</a> +<a class="jxr_linenumber" name="L19" href="#L19">19</a> <strong class="jxr_keyword">import</strong> java.util.stream.Stream; +<a class="jxr_linenumber" name="L20" href="#L20">20</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.ParameterizedTest; +<a class="jxr_linenumber" name="L21" href="#L21">21</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.Arguments; +<a class="jxr_linenumber" name="L22" href="#L22">22</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.CsvSource; +<a class="jxr_linenumber" name="L23" href="#L23">23</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.MethodSource; +<a class="jxr_linenumber" name="L24" href="#L24">24</a> +<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"> * Test cases for {@link NakagamiDistribution}.</em> +<a class="jxr_linenumber" name="L27" href="#L27">27</a> <em class="jxr_javadoccomment"> * Extends {@link BaseContinuousDistributionTest}. See javadoc of that class for details.</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> <strong class="jxr_keyword">class</strong> <a name="NakagamiDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/NakagamiDistributionTest.html#NakagamiDistributionTest">NakagamiDistributionTest</a> <strong class="jxr_keyword">extends</strong> <a name="BaseContinuousDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.html#BaseContinuousDistributionTest">BaseContinuousDistributionTest</a> { +<a class="jxr_linenumber" name="L30" href="#L30">30</a> @Override +<a class="jxr_linenumber" name="L31" href="#L31">31</a> ContinuousDistribution makeDistribution(Object... parameters) { +<a class="jxr_linenumber" name="L32" href="#L32">32</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mu = (Double) parameters[0]; +<a class="jxr_linenumber" name="L33" href="#L33">33</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> omega = (Double) parameters[1]; +<a class="jxr_linenumber" name="L34" href="#L34">34</a> <strong class="jxr_keyword">return</strong> NakagamiDistribution.of(mu, omega); +<a class="jxr_linenumber" name="L35" href="#L35">35</a> } +<a class="jxr_linenumber" name="L36" href="#L36">36</a> +<a class="jxr_linenumber" name="L37" href="#L37">37</a> @Override +<a class="jxr_linenumber" name="L38" href="#L38">38</a> Object[][] makeInvalidParameters() { +<a class="jxr_linenumber" name="L39" href="#L39">39</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> Object[][] { +<a class="jxr_linenumber" name="L40" href="#L40">40</a> {0.0, 1.0}, +<a class="jxr_linenumber" name="L41" href="#L41">41</a> {-0.1, 1.0}, +<a class="jxr_linenumber" name="L42" href="#L42">42</a> {0.5, 0.0}, +<a class="jxr_linenumber" name="L43" href="#L43">43</a> {0.5, -0.1} +<a class="jxr_linenumber" name="L44" href="#L44">44</a> }; +<a class="jxr_linenumber" name="L45" href="#L45">45</a> } +<a class="jxr_linenumber" name="L46" href="#L46">46</a> +<a class="jxr_linenumber" name="L47" href="#L47">47</a> @Override +<a class="jxr_linenumber" name="L48" href="#L48">48</a> String[] getParameterNames() { +<a class="jxr_linenumber" name="L49" href="#L49">49</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> String[] {<span class="jxr_string">"Shape"</span>, <span class="jxr_string">"Scale"</span>}; +<a class="jxr_linenumber" name="L50" href="#L50">50</a> } +<a class="jxr_linenumber" name="L51" href="#L51">51</a> +<a class="jxr_linenumber" name="L52" href="#L52">52</a> @Override +<a class="jxr_linenumber" name="L53" href="#L53">53</a> <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">double</strong> getRelativeTolerance() { +<a class="jxr_linenumber" name="L54" href="#L54">54</a> <strong class="jxr_keyword">return</strong> 5e-15; +<a class="jxr_linenumber" name="L55" href="#L55">55</a> } +<a class="jxr_linenumber" name="L56" href="#L56">56</a> +<a class="jxr_linenumber" name="L57" href="#L57">57</a> <em class="jxr_comment">//-------------------- Additional test cases -------------------------------</em> +<a class="jxr_linenumber" name="L58" href="#L58">58</a> +<a class="jxr_linenumber" name="L59" href="#L59">59</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L60" href="#L60">60</a> <em class="jxr_javadoccomment"> * Test additional moments.</em> +<a class="jxr_linenumber" name="L61" href="#L61">61</a> <em class="jxr_javadoccomment"> * Includes cases where {@code gamma(mu + 0.5) / gamma(mu)} is not computable</em> +<a class="jxr_linenumber" name="L62" href="#L62">62</a> <em class="jxr_javadoccomment"> * directly due to overflow of the gamma 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> @ParameterizedTest +<a class="jxr_linenumber" name="L65" href="#L65">65</a> @CsvSource({ +<a class="jxr_linenumber" name="L66" href="#L66">66</a> <em class="jxr_comment">// Generated using matlab</em> +<a class="jxr_linenumber" name="L67" href="#L67">67</a> <span class="jxr_string">"175, 0.75, 0.86540703592357171, 0.0010706621739778321"</span>, +<a class="jxr_linenumber" name="L68" href="#L68">68</a> <span class="jxr_string">"175, 1, 0.99928597029814059, 0.0014275495653037762"</span>, +<a class="jxr_linenumber" name="L69" href="#L69">69</a> <span class="jxr_string">"175, 1.25, 1.1172356792742391, 0.0017844369566297202"</span>, +<a class="jxr_linenumber" name="L70" href="#L70">70</a> <span class="jxr_string">"175, 3.75, 1.9351089605317091, 0.0053533108698891607"</span>, +<a class="jxr_linenumber" name="L71" href="#L71">71</a> <span class="jxr_string">"205.25, 0.75, 0.86549814380218737, 0.00091296307496802065"</span>, +<a class="jxr_linenumber" name="L72" href="#L72">72</a> <span class="jxr_string">"205.25, 1, 0.99939117261462862, 0.0012172840999573609"</span>, +<a class="jxr_linenumber" name="L73" href="#L73">73</a> <span class="jxr_string">"205.25, 1.25, 1.1173532990397681, 0.0015216051249467011"</span>, +<a class="jxr_linenumber" name="L74" href="#L74">74</a> <span class="jxr_string">"205.25, 3.75, 1.9353126839415795, 0.0045648153748401032"</span>, +<a class="jxr_linenumber" name="L75" href="#L75">75</a> <span class="jxr_string">"305.25, 0.75, 0.865670838787722, 0.00061399887256183283"</span>, +<a class="jxr_linenumber" name="L76" href="#L76">76</a> <span class="jxr_string">"305.25, 1.75, 1.32233404855355, 0.0014326640359776099"</span>, +<a class="jxr_linenumber" name="L77" href="#L77">77</a> <span class="jxr_string">"305.25, 3.75, 1.9356988416686078, 0.0030699943628091642"</span>, +<a class="jxr_linenumber" name="L78" href="#L78">78</a> <span class="jxr_string">"305.25, 12.75, 3.5692523053388152, 0.010437980833551158"</span>, +<a class="jxr_linenumber" name="L79" href="#L79">79</a> <span class="jxr_string">"305.25, 25.25, 5.0228805186490098, 0.020671295376248372"</span>, +<a class="jxr_linenumber" name="L80" href="#L80">80</a> }) +<a class="jxr_linenumber" name="L81" href="#L81">81</a> <strong class="jxr_keyword">void</strong> testAdditionalMoments(<strong class="jxr_keyword">double</strong> mu, <strong class="jxr_keyword">double</strong> omega, <strong class="jxr_keyword">double</strong> mean, <strong class="jxr_keyword">double</strong> variance) { +<a class="jxr_linenumber" name="L82" href="#L82">82</a> <em class="jxr_comment">// Note:</em> +<a class="jxr_linenumber" name="L83" href="#L83">83</a> <em class="jxr_comment">// The relative error of the variance is much greater than the mean.</em> +<a class="jxr_linenumber" name="L84" href="#L84">84</a> <em class="jxr_comment">// variance = omega - mean^2; omega > 0; x > 0; mean > 0</em> +<a class="jxr_linenumber" name="L85" href="#L85">85</a> <em class="jxr_comment">// This computation is subject to cancellation due to subtraction of two large</em> +<a class="jxr_linenumber" name="L86" href="#L86">86</a> <em class="jxr_comment">// values to approach a result of zero.</em> +<a class="jxr_linenumber" name="L87" href="#L87">87</a> <em class="jxr_comment">// Use a moderate threshold.</em> +<a class="jxr_linenumber" name="L88" href="#L88">88</a> <strong class="jxr_keyword">final</strong> <a name="DoubleTolerance" href="../../../../../org/apache/commons/statistics/distribution/DoubleTolerance.html#DoubleTolerance">DoubleTolerance</a> tolerance = createRelTolerance(2e-10); +<a class="jxr_linenumber" name="L89" href="#L89">89</a> <strong class="jxr_keyword">final</strong> NakagamiDistribution dist = NakagamiDistribution.of(mu, omega); +<a class="jxr_linenumber" name="L90" href="#L90">90</a> testMoments(dist, mean, variance, tolerance); +<a class="jxr_linenumber" name="L91" href="#L91">91</a> } +<a class="jxr_linenumber" name="L92" href="#L92">92</a> +<a class="jxr_linenumber" name="L93" href="#L93">93</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L94" href="#L94">94</a> <em class="jxr_javadoccomment"> * Repeat test of additional moments with alternative source for the expected result.</em> +<a class="jxr_linenumber" name="L95" href="#L95">95</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L96" href="#L96">96</a> @ParameterizedTest +<a class="jxr_linenumber" name="L97" href="#L97">97</a> @CsvSource({ +<a class="jxr_linenumber" name="L98" href="#L98">98</a> <em class="jxr_comment">// Generated using 128-bit quad precision implementation using Boost C++:</em> +<a class="jxr_linenumber" name="L99" href="#L99">99</a> <em class="jxr_comment">// #include <boost/multiprecision/float128.hpp></em> +<a class="jxr_linenumber" name="L100" href="#L100">100</a> <em class="jxr_comment">// #include <boost/math/special_functions/gamma.hpp></em> +<a class="jxr_linenumber" name="L101" href="#L101">101</a> <em class="jxr_comment">// #define quad boost::multiprecision::float128</em> +<a class="jxr_linenumber" name="L102" href="#L102">102</a> <em class="jxr_comment">// T v = boost::math::tgamma_delta_ratio(mu, T(0.5));</em> +<a class="jxr_linenumber" name="L103" href="#L103">103</a> <em class="jxr_comment">// T mean = sqrt(omega / mu) / v;</em> +<a class="jxr_linenumber" name="L104" href="#L104">104</a> <em class="jxr_comment">// T var = omega - (omega / mu) / v / v;</em> +<a class="jxr_linenumber" name="L105" href="#L105">105</a> <span class="jxr_string">"175, 0.75, 0.865407035923572335404337637742305354, 0.00107066217397678136642741884083229635"</span>, +<a class="jxr_linenumber" name="L106" href="#L106">106</a> <span class="jxr_string">"175, 1, 0.999285970298141244170512691211913862, 0.0014275495653023751552365584544430618"</span>, +<a class="jxr_linenumber" name="L107" href="#L107">107</a> <span class="jxr_string">"175, 1.25, 1.11723567927423980521693795242933784, 0.00178443695662796894404569806805382725"</span>, +<a class="jxr_linenumber" name="L108" href="#L108">108</a> <span class="jxr_string">"175, 3.75, 1.93510896053171023839534780723184735, 0.00535331086988390683213709420416109656"</span>, +<a class="jxr_linenumber" name="L109" href="#L109">109</a> <span class="jxr_string">"205.25, 0.75, 0.865498143802251959479795150977083271, 0.000912963074856388060643895128688537674"</span>, +<a class="jxr_linenumber" name="L110" href="#L110">110</a> <span class="jxr_string">"205.25, 1, 0.999391172614703197622376095323984551, 0.0012172840998085174141918601715848132"</span>, +<a class="jxr_linenumber" name="L111" href="#L111">111</a> <span class="jxr_string">"205.25, 1.25, 1.11735329903985129515900415713529348, 0.00152160512476064676773982521448079983"</span>, +<a class="jxr_linenumber" name="L112" href="#L112">112</a> <span class="jxr_string">"205.25, 3.75, 1.93531268394172368161190235734322469, 0.00456481537428194030321947564344316985"</span>, +<a class="jxr_linenumber" name="L113" href="#L113">113</a> <span class="jxr_string">"305.25, 0.75, 0.865670838787713729127832304174216151, 0.000613998872576147383115881187594898943"</span>, +<a class="jxr_linenumber" name="L114" href="#L114">114</a> <span class="jxr_string">"305.25, 1.75, 1.32233404855353739372707758901129787, 0.00143266403601101056060372277105460371"</span>, +<a class="jxr_linenumber" name="L115" href="#L115">115</a> <span class="jxr_string">"305.25, 3.75, 1.93569884166858953645398412102636382, 0.00306999436288073691557940593797382064"</span>, +<a class="jxr_linenumber" name="L116" href="#L116">116</a> <span class="jxr_string">"305.25, 12.75, 3.56925230533878138370667203279492999, 0.010437980833794505512969980189112608"</span>, +<a class="jxr_linenumber" name="L117" href="#L117">117</a> <span class="jxr_string">"305.25, 25.25, 5.02288051864896241877391197174369638, 0.0206712953767302952315679999823609879"</span>, +<a class="jxr_linenumber" name="L118" href="#L118">118</a> }) +<a class="jxr_linenumber" name="L119" href="#L119">119</a> <strong class="jxr_keyword">void</strong> testAdditionalMoments2(<strong class="jxr_keyword">double</strong> mu, <strong class="jxr_keyword">double</strong> omega, <strong class="jxr_keyword">double</strong> mean, <strong class="jxr_keyword">double</strong> variance) { +<a class="jxr_linenumber" name="L120" href="#L120">120</a> <em class="jxr_comment">// The mean is within 2 ULP.</em> +<a class="jxr_linenumber" name="L121" href="#L121">121</a> <em class="jxr_comment">// The variance is closer than the matlab result but the effect of cancellation</em> +<a class="jxr_linenumber" name="L122" href="#L122">122</a> <em class="jxr_comment">// prevents high accuracy.</em> +<a class="jxr_linenumber" name="L123" href="#L123">123</a> <strong class="jxr_keyword">final</strong> <a name="DoubleTolerance" href="../../../../../org/apache/commons/statistics/distribution/DoubleTolerance.html#DoubleTolerance">DoubleTolerance</a> tolerance = createRelTolerance(1e-12); +<a class="jxr_linenumber" name="L124" href="#L124">124</a> <strong class="jxr_keyword">final</strong> NakagamiDistribution dist = NakagamiDistribution.of(mu, omega); +<a class="jxr_linenumber" name="L125" href="#L125">125</a> testMoments(dist, mean, variance, tolerance); +<a class="jxr_linenumber" name="L126" href="#L126">126</a> } +<a class="jxr_linenumber" name="L127" href="#L127">127</a> +<a class="jxr_linenumber" name="L128" href="#L128">128</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L129" href="#L129">129</a> <em class="jxr_javadoccomment"> * Test log density where the density is zero.</em> +<a class="jxr_linenumber" name="L130" href="#L130">130</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L131" href="#L131">131</a> @ParameterizedTest +<a class="jxr_linenumber" name="L132" href="#L132">132</a> @MethodSource +<a class="jxr_linenumber" name="L133" href="#L133">133</a> <strong class="jxr_keyword">void</strong> testAdditionalLogDensity(<strong class="jxr_keyword">double</strong> mu, <strong class="jxr_keyword">double</strong> omega, <strong class="jxr_keyword">double</strong>[] x, <strong class="jxr_keyword">double</strong>[] expected) { +<a class="jxr_linenumber" name="L134" href="#L134">134</a> <strong class="jxr_keyword">final</strong> NakagamiDistribution dist = NakagamiDistribution.of(mu, omega); +<a class="jxr_linenumber" name="L135" href="#L135">135</a> testLogDensity(dist, x, expected, DoubleTolerances.relative(1e-15)); +<a class="jxr_linenumber" name="L136" href="#L136">136</a> } +<a class="jxr_linenumber" name="L137" href="#L137">137</a> +<a class="jxr_linenumber" name="L138" href="#L138">138</a> <strong class="jxr_keyword">static</strong> Stream<Arguments> testAdditionalLogDensity() { +<a class="jxr_linenumber" name="L139" href="#L139">139</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong>[] x = {50, 55, 60, 80, 120}; +<a class="jxr_linenumber" name="L140" href="#L140">140</a> <strong class="jxr_keyword">return</strong> Stream.of( +<a class="jxr_linenumber" name="L141" href="#L141">141</a> <em class="jxr_comment">// scipy.stats 1.9.3 (no support for omega):</em> +<a class="jxr_linenumber" name="L142" href="#L142">142</a> <em class="jxr_comment">// nakagami.logpdf(x, 0.5)</em> +<a class="jxr_linenumber" name="L143" href="#L143">143</a> Arguments.of(0.5, 1, x, +<a class="jxr_linenumber" name="L144" href="#L144">144</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-1250.2257913526448, -1512.7257913526448, -1800.2257913526448, +<a class="jxr_linenumber" name="L145" href="#L145">145</a> -3200.2257913526446, -7200.225791352645}), +<a class="jxr_linenumber" name="L146" href="#L146">146</a> <em class="jxr_comment">// nakagami.logpdf(x, 1.5) (no support for omega)</em> +<a class="jxr_linenumber" name="L147" href="#L147">147</a> Arguments.of(1.5, 1, x, +<a class="jxr_linenumber" name="L148" href="#L148">148</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-3740.7538269087863, -4528.063206549177, -5390.389183795199, +<a class="jxr_linenumber" name="L149" href="#L149">149</a> -9589.813819650295, -21589.00288943408}), +<a class="jxr_linenumber" name="L150" href="#L150">150</a> <em class="jxr_comment">// R nakagami 1.1.0 package:</em> +<a class="jxr_linenumber" name="L151" href="#L151">151</a> <em class="jxr_comment">// print(dnaka(x, 0.5, 2, log=TRUE), digits=17)</em> +<a class="jxr_linenumber" name="L152" href="#L152">152</a> Arguments.of(0.5, 2, x, +<a class="jxr_linenumber" name="L153" href="#L153">153</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-625.57236494292476, -756.82236494292465, -900.57236494292465, +<a class="jxr_linenumber" name="L154" href="#L154">154</a> -1600.57236494292442, -3600.57236494292420}), +<a class="jxr_linenumber" name="L155" href="#L155">155</a> <em class="jxr_comment">// print(dnaka(x, 0.5, 0.75, log=TRUE), digits=17)</em> +<a class="jxr_linenumber" name="L156" href="#L156">156</a> Arguments.of(0.5, 0.75, x, +<a class="jxr_linenumber" name="L157" href="#L157">157</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-1666.7486169830854, -2016.7486169830854, -2400.0819503164184, +<a class="jxr_linenumber" name="L158" href="#L158">158</a> -4266.7486169830854, -9600.0819503164203}), +<a class="jxr_linenumber" name="L159" href="#L159">159</a> <em class="jxr_comment">// print(dnaka(x, 1.5, 0.75, log=TRUE), digits=17)</em> +<a class="jxr_linenumber" name="L160" href="#L160">160</a> Arguments.of(1.5, 0.75, x, +<a class="jxr_linenumber" name="L161" href="#L161">161</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-4990.3223038001088, -6040.1316834404988, -7189.9576606865212, +<a class="jxr_linenumber" name="L162" href="#L162">162</a> -12789.3822965416184, -28788.5713663254028}), +<a class="jxr_linenumber" name="L163" href="#L163">163</a> <em class="jxr_comment">// print(dnaka(x, 1.5, 1.75, log=TRUE), digits=17)</em> +<a class="jxr_linenumber" name="L164" href="#L164">164</a> Arguments.of(1.5, 1.75, x, +<a class="jxr_linenumber" name="L165" href="#L165">165</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-2134.4503934478316, -2584.2597730882230, -3076.9428931913867, +<a class="jxr_linenumber" name="L166" href="#L166">166</a> -5476.3675290464835, -12332.6994559731247}), +<a class="jxr_linenumber" name="L167" href="#L167">167</a> <em class="jxr_comment">// print(dnaka(x, 1.5, 7.75, log=TRUE), digits=17)</em> +<a class="jxr_linenumber" name="L168" href="#L168">168</a> Arguments.of(1.5, 7.75, x, +<a class="jxr_linenumber" name="L169" href="#L169">169</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[]{-477.69633391576963, -579.11861678196749, -690.23491660863317, +<a class="jxr_linenumber" name="L170" href="#L170">170</a> -1231.59503633469740, -2779.17120289267450}) +<a class="jxr_linenumber" name="L171" href="#L171">171</a> ); +<a class="jxr_linenumber" name="L172" href="#L172">172</a> } +<a class="jxr_linenumber" name="L173" href="#L173">173</a> } +</pre> +<hr/> +<div id="footer">Copyright © 2018–2022 <a href="https://www.apache.org/";>The Apache Software Foundation</a>. All rights reserved.</div> +</body> +</html>
Added: dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NormalDistributionTest.html ============================================================================== --- dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NormalDistributionTest.html (added) +++ dev/commons/statistics/1.0-RC1/site/xref-test/org/apache/commons/statistics/distribution/NormalDistributionTest.html Thu Dec 1 16:47:12 2022 @@ -0,0 +1,219 @@ +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd";> +<html xmlns="http://www.w3.org/1999/xhtml"; xml:lang="en" lang="en"> +<head><meta http-equiv="content-type" content="text/html; charset=UTF-8" /> +<title>NormalDistributionTest xref</title> +<link type="text/css" rel="stylesheet" href="../../../../../stylesheet.css" /> +</head> +<body> +<div id="overview"><a href="../../../../../../testapidocs/org/apache/commons/statistics/distribution/NormalDistributionTest.html">View Javadoc</a></div><pre> +<a class="jxr_linenumber" name="L1" href="#L1">1</a> <em class="jxr_comment">/*</em> +<a class="jxr_linenumber" name="L2" href="#L2">2</a> <em class="jxr_comment"> * Licensed to the Apache Software Foundation (ASF) under one or more</em> +<a class="jxr_linenumber" name="L3" href="#L3">3</a> <em class="jxr_comment"> * contributor license agreements. See the NOTICE file distributed with</em> +<a class="jxr_linenumber" name="L4" href="#L4">4</a> <em class="jxr_comment"> * this work for additional information regarding copyright ownership.</em> +<a class="jxr_linenumber" name="L5" href="#L5">5</a> <em class="jxr_comment"> * The ASF licenses this file to You under the Apache License, Version 2.0</em> +<a class="jxr_linenumber" name="L6" href="#L6">6</a> <em class="jxr_comment"> * (the "License"); you may not use this file except in compliance with</em> +<a class="jxr_linenumber" name="L7" href="#L7">7</a> <em class="jxr_comment"> * the License. You may obtain a copy of the License at</em> +<a class="jxr_linenumber" name="L8" href="#L8">8</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L9" href="#L9">9</a> <em class="jxr_comment"> * <a href="http://www.apache.org/licenses/LICENSE-2.0"; target="alexandria_uri">http://www.apache.org/licenses/LICENSE-2.0</a></em> +<a class="jxr_linenumber" name="L10" href="#L10">10</a> <em class="jxr_comment"> *</em> +<a class="jxr_linenumber" name="L11" href="#L11">11</a> <em class="jxr_comment"> * Unless required by applicable law or agreed to in writing, software</em> +<a class="jxr_linenumber" name="L12" href="#L12">12</a> <em class="jxr_comment"> * distributed under the License is distributed on an "AS IS" BASIS,</em> +<a class="jxr_linenumber" name="L13" href="#L13">13</a> <em class="jxr_comment"> * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</em> +<a class="jxr_linenumber" name="L14" href="#L14">14</a> <em class="jxr_comment"> * See the License for the specific language governing permissions and</em> +<a class="jxr_linenumber" name="L15" href="#L15">15</a> <em class="jxr_comment"> * limitations under the License.</em> +<a class="jxr_linenumber" name="L16" href="#L16">16</a> <em class="jxr_comment"> */</em> +<a class="jxr_linenumber" name="L17" href="#L17">17</a> +<a class="jxr_linenumber" name="L18" href="#L18">18</a> <strong class="jxr_keyword">package</strong> org.apache.commons.statistics.distribution; +<a class="jxr_linenumber" name="L19" href="#L19">19</a> +<a class="jxr_linenumber" name="L20" href="#L20">20</a> <strong class="jxr_keyword">import</strong> java.math.BigDecimal; +<a class="jxr_linenumber" name="L21" href="#L21">21</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Assertions; +<a class="jxr_linenumber" name="L22" href="#L22">22</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.api.Test; +<a class="jxr_linenumber" name="L23" href="#L23">23</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.ParameterizedTest; +<a class="jxr_linenumber" name="L24" href="#L24">24</a> <strong class="jxr_keyword">import</strong> org.junit.jupiter.params.provider.CsvFileSource; +<a class="jxr_linenumber" name="L25" href="#L25">25</a> +<a class="jxr_linenumber" name="L26" href="#L26">26</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L27" href="#L27">27</a> <em class="jxr_javadoccomment"> * Test cases for {@link NormalDistribution}.</em> +<a class="jxr_linenumber" name="L28" href="#L28">28</a> <em class="jxr_javadoccomment"> * Extends {@link BaseContinuousDistributionTest}. See javadoc of that class for details.</em> +<a class="jxr_linenumber" name="L29" href="#L29">29</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L30" href="#L30">30</a> <strong class="jxr_keyword">class</strong> <a name="NormalDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/NormalDistributionTest.html#NormalDistributionTest">NormalDistributionTest</a> <strong class="jxr_keyword">extends</strong> <a name="BaseContinuousDistributionTest" href="../../../../../org/apache/commons/statistics/distribution/BaseContinuousDistributionTest.html#BaseContinuousDistributionTest">BaseContinuousDistributionTest</a> { +<a class="jxr_linenumber" name="L31" href="#L31">31</a> <em class="jxr_javadoccomment">/** A standard normal distribution used for calculations.</em> +<a class="jxr_linenumber" name="L32" href="#L32">32</a> <em class="jxr_javadoccomment"> * This is immutable and thread-safe and can be used across instances. */</em> +<a class="jxr_linenumber" name="L33" href="#L33">33</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">final</strong> NormalDistribution STANDARD_NORMAL = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L34" href="#L34">34</a> +<a class="jxr_linenumber" name="L35" href="#L35">35</a> @Override +<a class="jxr_linenumber" name="L36" href="#L36">36</a> ContinuousDistribution makeDistribution(Object... parameters) { +<a class="jxr_linenumber" name="L37" href="#L37">37</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> mean = (Double) parameters[0]; +<a class="jxr_linenumber" name="L38" href="#L38">38</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> sd = (Double) parameters[1]; +<a class="jxr_linenumber" name="L39" href="#L39">39</a> <strong class="jxr_keyword">return</strong> NormalDistribution.of(mean, sd); +<a class="jxr_linenumber" name="L40" href="#L40">40</a> } +<a class="jxr_linenumber" name="L41" href="#L41">41</a> +<a class="jxr_linenumber" name="L42" href="#L42">42</a> @Override +<a class="jxr_linenumber" name="L43" href="#L43">43</a> Object[][] makeInvalidParameters() { +<a class="jxr_linenumber" name="L44" href="#L44">44</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> Object[][] { +<a class="jxr_linenumber" name="L45" href="#L45">45</a> {0.0, 0.0}, +<a class="jxr_linenumber" name="L46" href="#L46">46</a> {0.0, -0.1} +<a class="jxr_linenumber" name="L47" href="#L47">47</a> }; +<a class="jxr_linenumber" name="L48" href="#L48">48</a> } +<a class="jxr_linenumber" name="L49" href="#L49">49</a> +<a class="jxr_linenumber" name="L50" href="#L50">50</a> @Override +<a class="jxr_linenumber" name="L51" href="#L51">51</a> String[] getParameterNames() { +<a class="jxr_linenumber" name="L52" href="#L52">52</a> <strong class="jxr_keyword">return</strong> <strong class="jxr_keyword">new</strong> String[] {<span class="jxr_string">"Mean"</span>, <span class="jxr_string">"StandardDeviation"</span>}; +<a class="jxr_linenumber" name="L53" href="#L53">53</a> } +<a class="jxr_linenumber" name="L54" href="#L54">54</a> +<a class="jxr_linenumber" name="L55" href="#L55">55</a> @Override +<a class="jxr_linenumber" name="L56" href="#L56">56</a> <strong class="jxr_keyword">protected</strong> <strong class="jxr_keyword">double</strong> getRelativeTolerance() { +<a class="jxr_linenumber" name="L57" href="#L57">57</a> <em class="jxr_comment">// Tolerance is 2.220446049250313E-15</em> +<a class="jxr_linenumber" name="L58" href="#L58">58</a> <strong class="jxr_keyword">return</strong> 10 * RELATIVE_EPS; +<a class="jxr_linenumber" name="L59" href="#L59">59</a> } +<a class="jxr_linenumber" name="L60" href="#L60">60</a> +<a class="jxr_linenumber" name="L61" href="#L61">61</a> <em class="jxr_comment">//-------------------- Additional test cases -------------------------------</em> +<a class="jxr_linenumber" name="L62" href="#L62">62</a> +<a class="jxr_linenumber" name="L63" href="#L63">63</a> @Test +<a class="jxr_linenumber" name="L64" href="#L64">64</a> <strong class="jxr_keyword">void</strong> testCumulativeProbabilityExtremes() { +<a class="jxr_linenumber" name="L65" href="#L65">65</a> <strong class="jxr_keyword">final</strong> NormalDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L66" href="#L66">66</a> testCumulativeProbability(dist, +<a class="jxr_linenumber" name="L67" href="#L67">67</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[] {-Double.MAX_VALUE, Double.MAX_VALUE, +<a class="jxr_linenumber" name="L68" href="#L68">68</a> Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY}, +<a class="jxr_linenumber" name="L69" href="#L69">69</a> <strong class="jxr_keyword">new</strong> <strong class="jxr_keyword">double</strong>[] {0, 1, 0, 1}, +<a class="jxr_linenumber" name="L70" href="#L70">70</a> DoubleTolerances.equals()); +<a class="jxr_linenumber" name="L71" href="#L71">71</a> } +<a class="jxr_linenumber" name="L72" href="#L72">72</a> +<a class="jxr_linenumber" name="L73" href="#L73">73</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L74" href="#L74">74</a> <em class="jxr_javadoccomment"> * Check to make sure top-coding of extreme values works correctly.</em> +<a class="jxr_linenumber" name="L75" href="#L75">75</a> <em class="jxr_javadoccomment"> * Verifies fixes for JIRA MATH-167, MATH-414.</em> +<a class="jxr_linenumber" name="L76" href="#L76">76</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L77" href="#L77">77</a> @Test +<a class="jxr_linenumber" name="L78" href="#L78">78</a> <strong class="jxr_keyword">void</strong> testLowerTail() { +<a class="jxr_linenumber" name="L79" href="#L79">79</a> <strong class="jxr_keyword">final</strong> NormalDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L80" href="#L80">80</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i < 100; i++) { <em class="jxr_comment">// make sure no convergence exception</em> +<a class="jxr_linenumber" name="L81" href="#L81">81</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> cdf = dist.cumulativeProbability(-i); +<a class="jxr_linenumber" name="L82" href="#L82">82</a> <strong class="jxr_keyword">if</strong> (i < 39) { <em class="jxr_comment">// make sure not top-coded</em> +<a class="jxr_linenumber" name="L83" href="#L83">83</a> Assertions.assertTrue(cdf > 0); +<a class="jxr_linenumber" name="L84" href="#L84">84</a> } <strong class="jxr_keyword">else</strong> { <em class="jxr_comment">// make sure top coding not reversed</em> +<a class="jxr_linenumber" name="L85" href="#L85">85</a> Assertions.assertEquals(0, cdf); +<a class="jxr_linenumber" name="L86" href="#L86">86</a> } +<a class="jxr_linenumber" name="L87" href="#L87">87</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> sf = dist.survivalProbability(-i); +<a class="jxr_linenumber" name="L88" href="#L88">88</a> <strong class="jxr_keyword">if</strong> (i < 9) { <em class="jxr_comment">// make sure not top-coded</em> +<a class="jxr_linenumber" name="L89" href="#L89">89</a> Assertions.assertTrue(sf < 1); +<a class="jxr_linenumber" name="L90" href="#L90">90</a> } <strong class="jxr_keyword">else</strong> { <em class="jxr_comment">// make sure top coding not reversed</em> +<a class="jxr_linenumber" name="L91" href="#L91">91</a> Assertions.assertEquals(1, sf); +<a class="jxr_linenumber" name="L92" href="#L92">92</a> } +<a class="jxr_linenumber" name="L93" href="#L93">93</a> } +<a class="jxr_linenumber" name="L94" href="#L94">94</a> } +<a class="jxr_linenumber" name="L95" href="#L95">95</a> +<a class="jxr_linenumber" name="L96" href="#L96">96</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L97" href="#L97">97</a> <em class="jxr_javadoccomment"> * Check to make sure top-coding of extreme values works correctly.</em> +<a class="jxr_linenumber" name="L98" href="#L98">98</a> <em class="jxr_javadoccomment"> * Verifies fixes for JIRA MATH-167, MATH-414.</em> +<a class="jxr_linenumber" name="L99" href="#L99">99</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L100" href="#L100">100</a> @Test +<a class="jxr_linenumber" name="L101" href="#L101">101</a> <strong class="jxr_keyword">void</strong> testUpperTail() { +<a class="jxr_linenumber" name="L102" href="#L102">102</a> <strong class="jxr_keyword">final</strong> NormalDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L103" href="#L103">103</a> <strong class="jxr_keyword">for</strong> (<strong class="jxr_keyword">int</strong> i = 0; i < 100; i++) { <em class="jxr_comment">// make sure no convergence exception</em> +<a class="jxr_linenumber" name="L104" href="#L104">104</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> cdf = dist.cumulativeProbability(i); +<a class="jxr_linenumber" name="L105" href="#L105">105</a> <strong class="jxr_keyword">if</strong> (i < 9) { <em class="jxr_comment">// make sure not top-coded</em> +<a class="jxr_linenumber" name="L106" href="#L106">106</a> Assertions.assertTrue(cdf < 1); +<a class="jxr_linenumber" name="L107" href="#L107">107</a> } <strong class="jxr_keyword">else</strong> { <em class="jxr_comment">// make sure top coding not reversed</em> +<a class="jxr_linenumber" name="L108" href="#L108">108</a> Assertions.assertEquals(1, cdf); +<a class="jxr_linenumber" name="L109" href="#L109">109</a> } +<a class="jxr_linenumber" name="L110" href="#L110">110</a> <em class="jxr_comment">// Test survival probability</em> +<a class="jxr_linenumber" name="L111" href="#L111">111</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> sf = dist.survivalProbability(i); +<a class="jxr_linenumber" name="L112" href="#L112">112</a> <strong class="jxr_keyword">if</strong> (i < 39) { <em class="jxr_comment">// make sure not top-coded</em> +<a class="jxr_linenumber" name="L113" href="#L113">113</a> Assertions.assertTrue(sf > 0); +<a class="jxr_linenumber" name="L114" href="#L114">114</a> } <strong class="jxr_keyword">else</strong> { <em class="jxr_comment">// make sure top coding not reversed</em> +<a class="jxr_linenumber" name="L115" href="#L115">115</a> Assertions.assertEquals(0, sf); +<a class="jxr_linenumber" name="L116" href="#L116">116</a> } +<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> +<a class="jxr_linenumber" name="L120" href="#L120">120</a> @Test +<a class="jxr_linenumber" name="L121" href="#L121">121</a> <strong class="jxr_keyword">void</strong> testMath1257() { +<a class="jxr_linenumber" name="L122" href="#L122">122</a> <strong class="jxr_keyword">final</strong> ContinuousDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L123" href="#L123">123</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> x = -10; +<a class="jxr_linenumber" name="L124" href="#L124">124</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> expected = 7.61985e-24; +<a class="jxr_linenumber" name="L125" href="#L125">125</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> v = dist.cumulativeProbability(x); +<a class="jxr_linenumber" name="L126" href="#L126">126</a> Assertions.assertEquals(1.0, v / expected, 1e-5); +<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> @Test +<a class="jxr_linenumber" name="L130" href="#L130">130</a> <strong class="jxr_keyword">void</strong> testMath280() { +<a class="jxr_linenumber" name="L131" href="#L131">131</a> <strong class="jxr_keyword">final</strong> NormalDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L132" href="#L132">132</a> <em class="jxr_comment">// Tolerance limited by precision of p close to 1.</em> +<a class="jxr_linenumber" name="L133" href="#L133">133</a> <em class="jxr_comment">// Lower the tolerance as the p value approaches 1.</em> +<a class="jxr_linenumber" name="L134" href="#L134">134</a> <strong class="jxr_keyword">double</strong> result; +<a class="jxr_linenumber" name="L135" href="#L135">135</a> result = dist.inverseCumulativeProbability(0.841344746068543); +<a class="jxr_linenumber" name="L136" href="#L136">136</a> TestUtils.assertEquals(1.0, result, createRelTolerance(1e-15)); +<a class="jxr_linenumber" name="L137" href="#L137">137</a> result = dist.inverseCumulativeProbability(0.9772498680518209); +<a class="jxr_linenumber" name="L138" href="#L138">138</a> TestUtils.assertEquals(2.0, result, createRelTolerance(1e-14)); +<a class="jxr_linenumber" name="L139" href="#L139">139</a> result = dist.inverseCumulativeProbability(0.9986501019683698); +<a class="jxr_linenumber" name="L140" href="#L140">140</a> TestUtils.assertEquals(3.0, result, createRelTolerance(1e-13)); +<a class="jxr_linenumber" name="L141" href="#L141">141</a> result = dist.inverseCumulativeProbability(0.9999683287581673); +<a class="jxr_linenumber" name="L142" href="#L142">142</a> TestUtils.assertEquals(4.0, result, createRelTolerance(1e-12)); +<a class="jxr_linenumber" name="L143" href="#L143">143</a> } +<a class="jxr_linenumber" name="L144" href="#L144">144</a> +<a class="jxr_linenumber" name="L145" href="#L145">145</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L146" href="#L146">146</a> <em class="jxr_javadoccomment"> * Test the inverse CDF is supported through the entire range of small values</em> +<a class="jxr_linenumber" name="L147" href="#L147">147</a> <em class="jxr_javadoccomment"> * that can be computed by the CDF. Approximate limit is x down to -38</em> +<a class="jxr_linenumber" name="L148" href="#L148">148</a> <em class="jxr_javadoccomment"> * (CDF around 2.8854e-316).</em> +<a class="jxr_linenumber" name="L149" href="#L149">149</a> <em class="jxr_javadoccomment"> * Verifies fix for STATISTICS-37.</em> +<a class="jxr_linenumber" name="L150" href="#L150">150</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L151" href="#L151">151</a> @Test +<a class="jxr_linenumber" name="L152" href="#L152">152</a> <strong class="jxr_keyword">void</strong> testInverseCDF() { +<a class="jxr_linenumber" name="L153" href="#L153">153</a> <strong class="jxr_keyword">final</strong> NormalDistribution dist = NormalDistribution.of(0, 1); +<a class="jxr_linenumber" name="L154" href="#L154">154</a> Assertions.assertEquals(0.0, dist.inverseCumulativeProbability(0.5)); +<a class="jxr_linenumber" name="L155" href="#L155">155</a> <em class="jxr_comment">// Get smaller and the CDF should reduce.</em> +<a class="jxr_linenumber" name="L156" href="#L156">156</a> <strong class="jxr_keyword">double</strong> x = 0; +<a class="jxr_linenumber" name="L157" href="#L157">157</a> <strong class="jxr_keyword">for</strong> (;;) { +<a class="jxr_linenumber" name="L158" href="#L158">158</a> x -= 1; +<a class="jxr_linenumber" name="L159" href="#L159">159</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> cdf = dist.cumulativeProbability(x); +<a class="jxr_linenumber" name="L160" href="#L160">160</a> <strong class="jxr_keyword">if</strong> (cdf == 0) { +<a class="jxr_linenumber" name="L161" href="#L161">161</a> <strong class="jxr_keyword">break</strong>; +<a class="jxr_linenumber" name="L162" href="#L162">162</a> } +<a class="jxr_linenumber" name="L163" href="#L163">163</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> x0 = dist.inverseCumulativeProbability(cdf); +<a class="jxr_linenumber" name="L164" href="#L164">164</a> <em class="jxr_comment">// Must be close</em> +<a class="jxr_linenumber" name="L165" href="#L165">165</a> Assertions.assertEquals(x, x0, Math.abs(x) * 1e-11, () -> <span class="jxr_string">"CDF = "</span> + cdf); +<a class="jxr_linenumber" name="L166" href="#L166">166</a> } +<a class="jxr_linenumber" name="L167" href="#L167">167</a> } +<a class="jxr_linenumber" name="L168" href="#L168">168</a> +<a class="jxr_linenumber" name="L169" href="#L169">169</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L170" href="#L170">170</a> <em class="jxr_javadoccomment"> * Test the PDF using high-accuracy uniform x data.</em> +<a class="jxr_linenumber" name="L171" href="#L171">171</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L172" href="#L172">172</a> <em class="jxr_javadoccomment"> * <p>This dataset uses uniformly spaced machine representable x values that have no</em> +<a class="jxr_linenumber" name="L173" href="#L173">173</a> <em class="jxr_javadoccomment"> * round-off component when squared. If the density is implemented using</em> +<a class="jxr_linenumber" name="L174" href="#L174">174</a> <em class="jxr_javadoccomment"> * {@code exp(logDensity(x))} the test will fail. Using the log density requires a</em> +<a class="jxr_linenumber" name="L175" href="#L175">175</a> <em class="jxr_javadoccomment"> * tolerance of approximately 53 ULP to pass the test of larger x values.</em> +<a class="jxr_linenumber" name="L176" href="#L176">176</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L177" href="#L177">177</a> @ParameterizedTest +<a class="jxr_linenumber" name="L178" href="#L178">178</a> @CsvFileSource(resources = <span class="jxr_string">"normpdf.csv"</span>) +<a class="jxr_linenumber" name="L179" href="#L179">179</a> <strong class="jxr_keyword">void</strong> testPDF(<strong class="jxr_keyword">double</strong> x, BigDecimal expected) { +<a class="jxr_linenumber" name="L180" href="#L180">180</a> assertPDF(x, expected, 2); +<a class="jxr_linenumber" name="L181" href="#L181">181</a> } +<a class="jxr_linenumber" name="L182" href="#L182">182</a> +<a class="jxr_linenumber" name="L183" href="#L183">183</a> <em class="jxr_javadoccomment">/**</em> +<a class="jxr_linenumber" name="L184" href="#L184">184</a> <em class="jxr_javadoccomment"> * Test the PDF using high-accuracy random x data.</em> +<a class="jxr_linenumber" name="L185" href="#L185">185</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L186" href="#L186">186</a> <em class="jxr_javadoccomment"> * <p>This dataset uses random x values with full usage of the 52-bit mantissa to ensure</em> +<a class="jxr_linenumber" name="L187" href="#L187">187</a> <em class="jxr_javadoccomment"> * that there is a round-off component when squared. It requires a high precision exponential</em> +<a class="jxr_linenumber" name="L188" href="#L188">188</a> <em class="jxr_javadoccomment"> * function using the round-off to compute {@code exp(-0.5*x*x)} accurately.</em> +<a class="jxr_linenumber" name="L189" href="#L189">189</a> <em class="jxr_javadoccomment"> * Using a standard precision computation requires a tolerance of approximately 383 ULP</em> +<a class="jxr_linenumber" name="L190" href="#L190">190</a> <em class="jxr_javadoccomment"> * to pass the test of larger x values.</em> +<a class="jxr_linenumber" name="L191" href="#L191">191</a> <em class="jxr_javadoccomment"> *</em> +<a class="jxr_linenumber" name="L192" href="#L192">192</a> <em class="jxr_javadoccomment"> * <p>See STATISTICS-52.</em> +<a class="jxr_linenumber" name="L193" href="#L193">193</a> <em class="jxr_javadoccomment"> */</em> +<a class="jxr_linenumber" name="L194" href="#L194">194</a> @ParameterizedTest +<a class="jxr_linenumber" name="L195" href="#L195">195</a> @CsvFileSource(resources = <span class="jxr_string">"normpdf2.csv"</span>) +<a class="jxr_linenumber" name="L196" href="#L196">196</a> <strong class="jxr_keyword">void</strong> testPDF2(<strong class="jxr_keyword">double</strong> x, BigDecimal expected) { +<a class="jxr_linenumber" name="L197" href="#L197">197</a> assertPDF(x, expected, 3); +<a class="jxr_linenumber" name="L198" href="#L198">198</a> } +<a class="jxr_linenumber" name="L199" href="#L199">199</a> +<a class="jxr_linenumber" name="L200" href="#L200">200</a> <strong class="jxr_keyword">private</strong> <strong class="jxr_keyword">static</strong> <strong class="jxr_keyword">void</strong> assertPDF(<strong class="jxr_keyword">double</strong> x, BigDecimal expected, <strong class="jxr_keyword">int</strong> ulpTolerance) { +<a class="jxr_linenumber" name="L201" href="#L201">201</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> e = expected.doubleValue(); +<a class="jxr_linenumber" name="L202" href="#L202">202</a> <strong class="jxr_keyword">final</strong> <strong class="jxr_keyword">double</strong> a = STANDARD_NORMAL.density(x); +<a class="jxr_linenumber" name="L203" href="#L203">203</a> Assertions.assertEquals(e, a, Math.ulp(e) * ulpTolerance, +<a class="jxr_linenumber" name="L204" href="#L204">204</a> () -> <span class="jxr_string">"ULP error: "</span> + expected.subtract(<strong class="jxr_keyword">new</strong> BigDecimal(a)).doubleValue() / Math.ulp(e)); +<a class="jxr_linenumber" name="L205" href="#L205">205</a> } +<a class="jxr_linenumber" name="L206" href="#L206">206</a> } +</pre> +<hr/> +<div id="footer">Copyright © 2018–2022 <a href="https://www.apache.org/";>The Apache Software Foundation</a>. All rights reserved.</div> +</body> +</html>
