# Re: [R] Empirical density estimation

```On 3/11/2018 3:35 PM, Christofer Bogaso wrote:
```
```But for my reporting purpose, I need to generate a bell curve like
plot based on empirical PDF, that also contains original points.```
```
Any idea would be helpful. Thanks,

```
```

Christofer,

something like the following may get you what you want:

## get the kernel density estimate
dens <- density(Dat)

## estimate the density at your original points
dnew <- approx(dens\$x,dens\$y,xout=Dat)

## plot kernel density estimate
plot(dx)

points(dnew, pch=1, cex=0.5, col="red")

Dan

--
Daniel Nordlund
Port Townsend, WA  USA

```
```On Mon, Mar 12, 2018 at 3:49 AM, Bert Gunter <bgunter.4...@gmail.com> wrote:
```
```You need to re-read ?density and perhaps think again -- or do some study --
about how a (kernel) density estimate works. The points at which the
estimate is calculated are *not* the values given, nor should they be!

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Sun, Mar 11, 2018 at 11:45 AM, Christofer Bogaso
<bogaso.christo...@gmail.com> wrote:
```
```
Hi,

Let say I have below vector of data-points :

Dat = c(-0.444444444444444, -0.25, -0.237449799196787, -0.227467046669042,

-0.227454464682363, -0.22, -0.214876033057851, -0.211781206171108,

-0.199891067538126, -0.192920353982301, -0.192307692307692,
-0.186046511627907,

-0.184418145956608, -0.181818181818182, -0.181818181818182,
-0.181266261925412,

-0.181003118503119, -0.179064587973274, -0.178217821782178,
-0.17809021675454,

-0.177685950413223, -0.177570093457944, -0.176470588235294,
-0.176470588235294,

-0.174825741611282, -0.168021680216802, -0.166666666666667,
-0.166666666666667,

-0.166380789022298, -0.164209115281501, -0.164011246485473,
-0.162689804772234,

-0.162361623616236, -0.160161507402423, -0.16, -0.155038759689922,

-0.154172560113154, -0.15311004784689, -0.151515151515152,
-0.151462994836489,

-0.151098901098901, -0.150537634408602, -0.150442477876106,
-0.150406504065041,

-0.149904214559387, -0.149882903981265, -0.149797570850202,
-0.148496240601504,

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-0.146989966555184,

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-0.14572864321608,

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-0.144021739130435,

-0.14375, -0.142212189616253, -0.141122913505311, -0.140324963072378,

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-0.136363636363636,

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-0.135135135135135,

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-0.131233595800525,

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-0.0305419952434597, -0.030406198638178, -0.0299651567944252,

-0.029945999018164, -0.0298786181139121, -0.0295741147960329,

-0.0293917033546227, -0.029171528588098, -0.0291327913279132,

-0.0290497291974397, -0.0288721376760064, -0.0287704170466792,

-0.0286236297198539, -0.0285714285714286, -0.0277575837684224,

-0.0277085471338513, -0.0275897304892068, -0.0275526742301458,

-0.027027027027027, -0.0270270270270269, -0.0269087523277468,

-0.0268918695148203, -0.02676704307821, -0.026454253142356,
-0.0263157894736842,

-0.0263157894736842, -0.0261660978384529, -0.025974025974026,

-0.0257503107796129, -0.0255319148936171, -0.0254237288135594,

-0.025297619047619, -0.0249174422095467, -0.0248888888888889,

-0.024767619719967, -0.0246053853296194, -0.0245269796776454,

-0.024390243902439, -0.0241935483870968, -0.0238907849829351,

-0.0238153295944078, -0.0234413496961306, -0.0232558139534884,

-0.0232558139534883, -0.0230392156862745, -0.0230360307147077,

-0.0228847365106026, -0.0225806451612903, -0.0224519940915805,

-0.0214786344110332, -0.0212360867018161, -0.0205245153933865,

-0.0204170602339606, -0.0200986321764215, -0.0200729927007299,

-0.0199828473413379, -0.0194174757281553, -0.0193536931818183,

-0.0192885771543086, -0.019222732971166, -0.0191414840759143,

-0.0189573459715641, -0.0188902007083826, -0.0186903321231681,

-0.0184456468273487, -0.0183066361556064, -0.0182166826462128,

-0.0181149908112366, -0.0179372197309418, -0.0179172441100772,

-0.0178571428571429, -0.0174672489082969, -0.0174216027874564,

-0.0171428571428572, -0.017017253604349, -0.0169252468265163,

-0.0165094339622642, -0.0158730158730158, -0.0158415841584159,

-0.0157247037374659, -0.0157089706490286, -0.0156250000000001,

-0.0153846153846153, -0.0151668351870576, -0.0151589242053789,

-0.0150489089541008, -0.0150262202501008, -0.0150081124932396,

-0.0148196281468128, -0.0144251166737377, -0.0142857142857142,

-0.0140638734251392, -0.0136986301369863, -0.0133333333333333,

-0.0129464285714286, -0.0129449838187702, -0.0127813811522321,

-0.0126030053320408, -0.0125721665147373, -0.0125, -0.0122160435399906,

-0.0122116689280869, -0.0121019108280255, -0.0118747750989563,

-0.0118277953189996, -0.0117107942973524, -0.0115172759138707,

-0.0114087997381585, -0.0113924050632912, -0.0111524163568772,

-0.0111248454882571, -0.0111111111111111, -0.0102570933795125,

-0.0102040816326532, -0.00963463463463469, -0.00958657878969439,

-0.00941028858218319, -0.00874453466583389, -0.00779588944011335,

-0.00713620850139625, -0.00710720027075056, -0.00709219858156026,

-0.00624999999999998, -0.00551977920883173, -0.00521499557217353,

-0.00453998797354176, -0.00444444444444444, -0.00166389351081533,

-0.00118483412322285, -0.00100704934541787, -0.000937500000000036,

0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,

0.000218031178458569, 0.000796495420151402, 0.00167130919220062,

0.00190476190476193, 0.00350058343057173, 0.00363914958820145,

0.00432900432900424, 0.00456037942356804, 0.00477446915441642,

0.0050825509873745, 0.00525691029336935, 0.00603318250377083,

0.00652173913043472, 0.00733192494097176, 0.00747663551401869,

0.00760456273764256, 0.00812529439472442, 0.00991231414410967,

0.0101685066821615, 0.0106182565507793, 0.0109070034443169,
0.0115183246073298,

0.0115442244823827, 0.0127659574468085, 0.0128076846107665,
0.0135135135135135,

0.0140845070422535, 0.0150730098916627, 0.0159362549800796,
0.0172413793103449,

0.0176899063475547, 0.0186954715413378, 0.0187765706188003,
0.0195757403189066,

0.019607843137255, 0.0199999999999999, 0.0210526315789473,
0.0221979621542939,

0.0239410681399632, 0.0239999999999999, 0.025149051490515,
0.0260869565217392,

0.0262475696694749, 0.028180542563143, 0.0285714285714286,
0.0303030303030302,

0.0315904139433552, 0.0341864716636198, 0.0375782881002089,
0.038479809976247,

0.0387596899224806, 0.0416666666666667, 0.0428100987925357,
0.0428134556574923,

0.0437201907790144, 0.0451127819548872, 0.0460251046025105,
0.0487779511180447,

0.048975188781014, 0.0529872938632063, 0.0562390158172233,
0.0589335827876521,

0.0617551462621885, 0.0628115653040877, 0.0671812464265294,
0.0721784776902887,

0.0736842105263157, 0.0833333333333334, 0.083862394802894,
0.0970464135021097,

0.0971168437025795, 0.102272727272727, 0.111111111111111,
0.117117117117117,

0.123532699832309, 0.141304347826087, 0.179487179487179,
0.191268191268191,

0.205128205128205, 0.219020172910663, 0.271590909090909, 0.333333333333333

)

Now I want to estimate empirical PDF for interval of (-1, 1) including
all points of Dat

I have looked into the density() function, however it appears that,
empirical density is estimated for equally distant points, which not
necessarily contains actual supplied points (in my case, Dat)

Is there any option to achieve the same?

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and provide commented, minimal, self-contained, reproducible code.
```
```

```
```
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```