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Author's title

Author*Unverified author*
R Software Modulerwasp_density.wasp
Title produced by softwareKernel Density Estimation
Date of computationThu, 29 May 2008 03:14:36 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/May/29/t1212052659gxrw1ckz2jegf1i.htm/, Retrieved Wed, 15 May 2024 12:31:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=13499, Retrieved Wed, 15 May 2024 12:31:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kernel Density Estimation] [Dichtheidsgrafiek...] [2008-05-29 09:14:36] [e3a9774fc191d7d42e3eb0422143859b] [Current]
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Dataseries X:
25
25
25
25
29
30
30
29
35
30
30
30
29
30
30
26
30
30
30
35
30
30
30
50
25
29
30
25
30
30
25
42
29
15
29
30
25
20
10
30
29
30
50
25
30
30
25
50
29
30
30
30
30
30
30
29
35
40
29
26
23
25
30
30
30
30
20
29
25
25
28
30
30
25
30
31
30
29
45
30
30
35
30
30
25
50
40
20
35
22
30
25
30
30
29
50
45
30
26
30
29
35
20
29
25
30
45
35
30
30
40
20
26
29
20
25
30
30
25
30
23
25
30
30
40
30
40
35
40
30
25
33
30
30
30
35
33
35
30
40
29
25
27
30
30
35
20
30
30
25
25
30
30
30
40
40
30
40
20
50
20
30
30
30
30
25
30
30
30
30
30
30
23
30
25
50
20
23
25
29
26
40
30
30
35
20
29
25
30
30
30
50
30
35
30
30
30
35
30
35
15
30
20
35
40
30
30
40
29
30
20
35
50
30
30
40
30
50
18
15
30
23
29
30
35
30
23
30
25
26
25
30
20
25
30
29
40
30
30
30
40
37
20
25
30
32
35
32
30
30
35
30
25
30
24
30
35
30
30
30
30
30
25
30
25
35
30
30
30
30
30
30
35
32
30
20
20
30
35
30
40
29
26
40
25
35
30
23
30
27
35
30
20
30
25
50
30
30
29
35
29
25
30
45
30
25
29
25
40
30
30
40
30
30
29
35
35
30
30
27
30
30
29
50
30
30
20
25
25
30
27
29
50
50
30
30
40
20
30
30
30
25
30
30
30
30
40
25
35
30
30
35
20
20
50
35
29
50
40
30
45
30
40
30
29
25
40
35
25
21
30
30
30
30
15
30
30
30
30
30
25
30
30
30
30
25
25
40
30
33
40
26
30
37
25
29
30
25
29
30
30
30
30
30
22
25
30
40
30
29
25
30
30
29
30
30
30
35
30
35
30
12
15
25
30
30
30
25
20
30
35
35
29
40
30
40
30
25
30
20
29
28
30
25
30
50
30
30
29
30
35
20
30
30
30
30
30
40
30
30
35
25
30
50
30
30
30
30
25
30
30
30
25
30
30
30
25
30
30
26
30
30
30
30
25
20
30
35
30
20
20
25
30
30
30
30
29
35
25
30
30
35
35
30
20
30
30
30
25
30
30
26
30
25
30
50
30
20
29
30
30
30
30
30
40
30
35
27
30
25
29
25
30
25
30
29
25
20
30
25
32
30
29
30
30
30
30
25
25
30
30
60
20
30
35
25
30
25
30
40
25
30
29
29
30
29
26
18
30
40
30
30
30
30
30
29
30
30
30
35
30
30
30
20
29
20
30
30
25
30
40
30
30
25
40
30
30
29
25
30
35
30
20
30
20
25
30
40
25
47
20
20
30
30
25
30
25
40
29
40
29
30
30
30
35
30
20
30
24
30
40
30
30
15
35
18
30
25
30
30
30
15
20
30
25
30
20
30
30
30
25
40
50
30
30
35
30
30
15
30
25
30
30
26
30
25
25
30
30
30
50
30
25
30
25
30
26
25
34
30
25
30
35
30
40
30
30
29
30
29
30
50
30
15
30
25
50
30
30
35
35
25
23
30
30
30
35
25
15
30
29
30
15
30
40
29
30
25
25
50
30
1
30
30
30
35
30
30
35
30
20
20
20
30
35
30
25
29
35
40
30
35
29
30
30
30
29
30
30
30
30
30
30
30
35
30
30
30
25
50
30
30
30
25
25
35
30
35
30
29
30
35
30
30
35
25
25
29
35
50
30
30
29
30
30
30
20
30
30
20
30
25
20
30
50
20
40
40
30
29
35
25
20
20
21
29
35
30
28
30
30
35
26
30
25
25
30
30
30
25
35
30
35
35
30
29
30
26
30
27
30
30
50
25
30
30
30
40
30
32
25
35
30
30
20
30
40
30
26
30
40
30
30
26
35
35
26
50
30
30
25
30
40
25
30
25
30
15
40
30
25
30
30
30
30
30
25
25
30
20
18
25
30
29
13
27
30
30
30
30
25
30
35
29
30
29
30
30
25
45
29
30
30
25
25
29
30
30
30
29
30
23
35
35
10
32
29
45
30
29
30
15
50
35
25
25
30
30
30
30
30
40
29
25
30
25
30
25
25
30
35
30
25
20
30
30
30
15
30
35
50
35
30
30
25
30
30
15
30
25
30
30
25
29
30
30
40
25
30
30
25
35
29
30
25
30
30
25
30
30
30
25
35
25
29
25
30
30
50
30
30

30
30
30
20
25
25
35
25
30
25
50
20
45
25
35
30
40
35
30
30
30
30
23
30
25
30
15
60
60




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13499&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13499&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13499&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Properties of Density Trace
Bandwidth0.672167744540826
#Observations1020

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 0.672167744540826 \tabularnewline
#Observations & 1020 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=13499&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]0.672167744540826[/C][/ROW]
[ROW][C]#Observations[/C][C]1020[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=13499&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=13499&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
Bandwidth0.672167744540826
#Observations1020



Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
bitmap(file='density1.png')
mydensity1<-density(x,kernel='gaussian',na.rm=TRUE)
plot(mydensity1,main='Gaussian Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
mydensity1
bitmap(file='density2.png')
mydensity2<-density(x,kernel='epanechnikov',na.rm=TRUE)
plot(mydensity2,main='Epanechnikov Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density3.png')
mydensity3<-density(x,kernel='rectangular',na.rm=TRUE)
plot(mydensity3,main='Rectangular Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density4.png')
mydensity4<-density(x,kernel='triangular',na.rm=TRUE)
plot(mydensity4,main='Triangular Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density5.png')
mydensity5<-density(x,kernel='biweight',na.rm=TRUE)
plot(mydensity5,main='Biweight Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density6.png')
mydensity6<-density(x,kernel='cosine',na.rm=TRUE)
plot(mydensity6,main='Cosine Kernel',xlab=xlab,ylab=ylab)
grid()
dev.off()
bitmap(file='density7.png')
mydensity7<-density(x,kernel='optcosine',na.rm=TRUE)
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')