## Free Statistics

of Irreproducible Research!

Author's title
Author*The author of this computation has been verified*
R Software Modulerwasp_density.wasp
Title produced by softwareKernel Density Estimation
Date of computationSat, 10 Nov 2012 07:43:48 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Nov/10/t1352551442y9yoiixhje7kik4.htm/, Retrieved Sat, 10 Dec 2022 04:33:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=187329, Retrieved Sat, 10 Dec 2022 04:33:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [workshop 6 4] [2012-11-10 11:48:34] [e31fe164d58995c48777312ee804d655]
- RMPD    [Kernel Density Estimation] [workshop 6 2 (1)] [2012-11-10 12:43:48] [de03d6ba395ecb425436b99f470cccc0] [Current]
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Dataseries X:
255
280.2
299.9
339.2
374.2
393.5
389.2
381.7
375.2
369
357.4
352.1
346.5
342.9
340.3
328.3
322.9
314.3
308.9
294
285.6
281.2
280.3
278.8
274.5
270.4
263.4
259.9
258
262.7
284.7
311.3
322.1
327
331.3
333.3
321.4
327
320
314.7
316.7
314.4
321.3
318.2
307.2
301.3
287.5
277.7
274.4
258.8
253.3
251
248.4
249.5
246.1
244.5
243.6
244
240.8
249.8
248
259.4
260.5
260.8
261.3
259.5
256.6
257.9
256.5
254.2
253.3
253.8
255.5
257.1
257.3
253.2
252.8
252
250.7
252.2
250
251
253.4
251.2
255.6
261.1
258.9
259.9
261.2
264.7
267.1
266.4
267.7
268.6
267.5
268.5
268.5
270.5
270.9
270.1
269.3
269.8
270.1
264.9
263.7
264.8
263.7
255.9
276.2
360.1
380.5
373.7
369.8
366.6
359.3
345.8
326.2
324.5
328.1
327.5
324.4
316.5
310.9
301.5
291.7
290.4
287.4
277.7
281.6
288
276
272.9
283
283.3
276.8
284.5
282.7
281.2
287.4
283.1
284
285.5
289.2
292.5
296.4
305.2
303.9
311.5
316.3
316.7
322.5
317.1
309.8
303.8
290.3
293.7
291.7
296.5
289.1
288.5
293.8
297.7
305.4
302.7
302.5
303
294.5
294.1
294.5
297.1
289.4
292.4
287.9
286.6
280.5
272.4
269.2
270.6
267.3
262.5
266.8
268.8
263.1
261.2
266
262.5
265.2
261.3
253.7
249.2
239.1
236.4
235.2
245.2
246.2
247.7
251.4
253.3
254.8
250
249.3
241.5
243.3
248
253
252.9
251.5
251.6
253.5
259.8
334.1
448
445.8
445
448.2
438.2
439.8
423.4
410.8
408.4
406.7
405.9
402.7
405.1
399.6
386.5
381.4
375.2
357.7
359
355
352.7
344.4
343.8
338
339
333.3
334.4
328.3
330.7
330
331.6
351.2
389.4
410.9
442.8
462.8
466.9
461.7
439.2
430.3
416.1
402.5
397.3
403.3
395.9
387.8
378.6
377.1
370.4
362
350.3
348.2
344.6
343.5
342.8
347.6
346.6
349.5
342.1
342
342.8
339.3
348.2
333.7
334.7
354
367.7
363.3
358.4
353.1
343.1
344.6
344.4
333.9
331.7
324.3
321.2
322.4
321.7
320.5
312.8
309.7
315.6
309.7
304.6
302.5
301.5
298.8
291.3
293.6
294.6
285.9
297.6
301.1
293.8
297.7
292.9
292.1
287.2
288.2
283.8
299.9
292.4
293.3
300.8
293.7
293.1
294.4
292.1
291.9
282.5
277.9
287.5
289.2
285.6
293.2
290.8
283.1
275
287.8
287.8
287.4
284
277.8
277.6
304.9
294
300.9
324
332.9
341.6
333.4
348.2
344.7
344.7
329.3
323.5
323.2
317.4
330.1
329.2
334.9
315.8
315.4
319.6
317.3
313.8
315.8
311.3

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 6 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187329&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187329&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187329&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 6 seconds R Server 'Gertrude Mary Cox' @ cox.wessa.net

 Properties of Density Trace Bandwidth 13.5297232370976 #Observations 360

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 13.5297232370976 \tabularnewline
#Observations & 360 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187329&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]13.5297232370976[/C][/ROW]
[ROW][C]#Observations[/C][C]360[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187329&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187329&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Properties of Density Trace Bandwidth 13.5297232370976 #Observations 360

 Maximum Density Values Kernel x-value max. density Gaussian 285.841500687856 0.00870635157585919 Epanechnikov 275.432632253054 0.00894581714085754 Rectangular 271.758913981948 0.00974132694374492 Triangular 277.269491388607 0.00866353844771497 Biweight 276.044918631572 0.00878540011679499 Cosine 276.65720501009 0.00873719119478196 Optcosine 275.432632253054 0.00889592646444589

\begin{tabular}{lllllllll}
\hline
Maximum Density Values \tabularnewline
Kernel & x-value & max. density \tabularnewline
Gaussian & 285.841500687856 & 0.00870635157585919 \tabularnewline
Epanechnikov & 275.432632253054 & 0.00894581714085754 \tabularnewline
Rectangular & 271.758913981948 & 0.00974132694374492 \tabularnewline
Triangular & 277.269491388607 & 0.00866353844771497 \tabularnewline
Biweight & 276.044918631572 & 0.00878540011679499 \tabularnewline
Cosine & 276.65720501009 & 0.00873719119478196 \tabularnewline
Optcosine & 275.432632253054 & 0.00889592646444589 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=187329&T=2

[TABLE]
[ROW][C]Maximum Density Values[/C][/ROW]
[ROW][C]Kernel[/C][C]x-value[/C][C]max. density[/C][/ROW]
[ROW][C]Gaussian[/C][C]285.841500687856[/C][C]0.00870635157585919[/C][/ROW]
[ROW][C]Epanechnikov[/C][C]275.432632253054[/C][C]0.00894581714085754[/C][/ROW]
[ROW][C]Rectangular[/C][C]271.758913981948[/C][C]0.00974132694374492[/C][/ROW]
[ROW][C]Triangular[/C][C]277.269491388607[/C][C]0.00866353844771497[/C][/ROW]
[ROW][C]Biweight[/C][C]276.044918631572[/C][C]0.00878540011679499[/C][/ROW]
[ROW][C]Cosine[/C][C]276.65720501009[/C][C]0.00873719119478196[/C][/ROW]
[ROW][C]Optcosine[/C][C]275.432632253054[/C][C]0.00889592646444589[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=187329&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=187329&T=2

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

 Maximum Density Values Kernel x-value max. density Gaussian 285.841500687856 0.00870635157585919 Epanechnikov 275.432632253054 0.00894581714085754 Rectangular 271.758913981948 0.00974132694374492 Triangular 277.269491388607 0.00866353844771497 Biweight 276.044918631572 0.00878540011679499 Cosine 276.65720501009 0.00873719119478196 Optcosine 275.432632253054 0.00889592646444589

if (par1 == '0') bw <- 'nrd0'if (par1 != '0') bw <- as.numeric(par1)par3 <- as.numeric(par3)mydensity <- array(NA, dim=c(par3,8))bitmap(file='density1.png')mydensity1<-density(x,bw=bw,kernel='gaussian',na.rm=TRUE)mydensity[,8] = signif(mydensity1$x,3)mydensity[,1] = signif(mydensity1$y,3)plot(mydensity1,main='Gaussian Kernel',xlab=xlab,ylab=ylab)grid()dev.off()mydensity1bitmap(file='density2.png')mydensity2<-density(x,bw=bw,kernel='epanechnikov',na.rm=TRUE)mydensity[,2] = signif(mydensity2$y,3)plot(mydensity2,main='Epanechnikov Kernel',xlab=xlab,ylab=ylab)grid()dev.off()bitmap(file='density3.png')mydensity3<-density(x,bw=bw,kernel='rectangular',na.rm=TRUE)mydensity[,3] = signif(mydensity3$y,3)plot(mydensity3,main='Rectangular Kernel',xlab=xlab,ylab=ylab)grid()dev.off()bitmap(file='density4.png')mydensity4<-density(x,bw=bw,kernel='triangular',na.rm=TRUE)mydensity[,4] = signif(mydensity4$y,3)plot(mydensity4,main='Triangular Kernel',xlab=xlab,ylab=ylab)grid()dev.off()bitmap(file='density5.png')mydensity5<-density(x,bw=bw,kernel='biweight',na.rm=TRUE)mydensity[,5] = signif(mydensity5$y,3)plot(mydensity5,main='Biweight Kernel',xlab=xlab,ylab=ylab)grid()dev.off()bitmap(file='density6.png')mydensity6<-density(x,bw=bw,kernel='cosine',na.rm=TRUE)mydensity[,6] = signif(mydensity6$y,3)plot(mydensity6,main='Cosine Kernel',xlab=xlab,ylab=ylab)grid()dev.off()bitmap(file='density7.png')mydensity7<-density(x,bw=bw,kernel='optcosine',na.rm=TRUE)mydensity[,7] = signif(mydensity7$y,3)plot(mydensity7,main='Optcosine Kernel',xlab=xlab,ylab=ylab)grid()dev.off()load(file='createtable')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Properties of Density Trace',2,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Bandwidth',header=TRUE)a<-table.element(a,mydensity1$bw)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'#Observations',header=TRUE)a<-table.element(a,mydensity1$n)a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable.tab')a<-table.start()a<-table.row.start(a)a<-table.element(a,'Maximum Density Values',3,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Kernel',1,TRUE)a<-table.element(a,'x-value',1,TRUE)a<-table.element(a,'max. density',1,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Gaussian',1,TRUE)a<-table.element(a,mydensity1$x[mydensity1$y==max(mydensity1$y)],1)a<-table.element(a,mydensity1$y[mydensity1$y==max(mydensity1$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Epanechnikov',1,TRUE)a<-table.element(a,mydensity2$x[mydensity2$y==max(mydensity2$y)],1)a<-table.element(a,mydensity2$y[mydensity2$y==max(mydensity2$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Rectangular',1,TRUE)a<-table.element(a,mydensity3$x[mydensity3$y==max(mydensity3$y)],1)a<-table.element(a,mydensity3$y[mydensity3$y==max(mydensity3$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Triangular',1,TRUE)a<-table.element(a,mydensity4$x[mydensity4$y==max(mydensity4$y)],1)a<-table.element(a,mydensity4$y[mydensity4$y==max(mydensity4$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Biweight',1,TRUE)a<-table.element(a,mydensity5$x[mydensity5$y==max(mydensity5$y)],1)a<-table.element(a,mydensity5$y[mydensity5$y==max(mydensity5$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Cosine',1,TRUE)a<-table.element(a,mydensity6$x[mydensity6$y==max(mydensity6$y)],1)a<-table.element(a,mydensity6$y[mydensity6$y==max(mydensity6$y)],1)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'Optcosine',1,TRUE)a<-table.element(a,mydensity7$x[mydensity7$y==max(mydensity7$y)],1)a<-table.element(a,mydensity7$y[mydensity7$y==max(mydensity7$y)],1)a<-table.row.end(a)a<-table.end(a)table.save(a,file='mytable2.tab')if (par2=='yes') {a<-table.start()a<-table.row.start(a)a<-table.element(a,'Kernel Density Values',8,TRUE)a<-table.row.end(a)a<-table.row.start(a)a<-table.element(a,'x-value',1,TRUE)a<-table.element(a,'Gaussian',1,TRUE)a<-table.element(a,'Epanechnikov',1,TRUE)a<-table.element(a,'Rectangular',1,TRUE)a<-table.element(a,'Triangular',1,TRUE)a<-table.element(a,'Biweight',1,TRUE)a<-table.element(a,'Cosine',1,TRUE)a<-table.element(a,'Optcosine',1,TRUE)a<-table.row.end(a)for(i in 1:par3) {a<-table.row.start(a)a<-table.element(a,mydensity[i,8],1,TRUE)for(j in 1:7) {a<-table.element(a,mydensity[i,j],1)}a<-table.row.end(a)}a<-table.end(a)table.save(a,file='mytable1.tab')}