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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_density.wasp
Title produced by softwareKernel Density Estimation
Date of computationSun, 16 Aug 2015 14:44:07 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Aug/16/t1439732663bvjzhe6bip4yj5p.htm/, Retrieved Sat, 18 May 2024 08:21:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=280139, Retrieved Sat, 18 May 2024 08:21:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kernel Density Estimation] [] [2015-08-16 13:44:07] [f898ec974b62c60a8bec4044c4c271e3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1 544 400
1 487 200
1 573 000
1 258 400
1 630 200
1 601 600
1 716 000
1 773 200
1 973 400
1 716 000
1 630 200
2 030 600
1 716 000
1 287 000
1 515 800
1 144 000
1 601 600
1 315 600
1 744 600
1 573 000
1 658 800
1 859 000
1 830 400
2 173 600
1 573 000
1 315 600
1 458 600
1 058 200
1 515 800
1 172 600
1 658 800
1 573 000
1 401 400
2 002 000
1 801 800
2 059 200
1 544 400
1 430 000
1 287 000
1 058 200
1 401 400
1 258 400
1 716 000
1 658 800
1 430 000
1 916 200
1 773 200
2 288 000
1 830 400
1 115 400
1 115 400
1 115 400
1 315 600
1 315 600
1 773 200
1 630 200
1 458 600
1 830 400
1 687 400
2 431 000
1 916 200
1 115 400
1 172 600
972 400
1 344 200
1 544 400
1 944 800
1 916 200
1 544 400
1 801 800
1 601 600
2 288 000
1 744 600
1 401 400
1 258 400
943 800
1 401 400
1 687 400
1 973 400
1 859 000
1 372 800
1 973 400
1 544 400
2 373 800
1 973 400
1 430 000
1 315 600
886 600
1 401 400
1 344 200
2 030 600
2 030 600
1 544 400
2 002 000
1 487 200
2 316 600
1 973 400
1 458 600
1 115 400
772 200
1 515 800
1 458 600
1 916 200
2 202 200
1 630 200
1 830 400
1 372 800
2 373 800

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280139&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]3 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=280139&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280139&T=0

As an alternative you can also use a QR Code:  
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 time3 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Properties of Density Trace
Bandwidth120486.662844916
#Observations108

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 120486.662844916 \tabularnewline
#Observations & 108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280139&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]120486.662844916[/C][/ROW]
[ROW][C]#Observations[/C][C]108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280139&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280139&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Properties of Density Trace
Bandwidth120486.662844916
#Observations108






Maximum Density Values
Kernelx-valuemax. density
Gaussian1538677.847963921.11209593457469e-06
Epanechnikov1515373.347209811.10782916438556e-06
Rectangular1515373.347209811.14689268067045e-06
Triangular1543338.748114741.11706856627938e-06
Biweight1529356.047662281.10781575212115e-06
Cosine1534016.94781311.10858154788731e-06
Optcosine1515373.347209811.10837336527179e-06

\begin{tabular}{lllllllll}
\hline
Maximum Density Values \tabularnewline
Kernel & x-value & max. density \tabularnewline
Gaussian & 1538677.84796392 & 1.11209593457469e-06 \tabularnewline
Epanechnikov & 1515373.34720981 & 1.10782916438556e-06 \tabularnewline
Rectangular & 1515373.34720981 & 1.14689268067045e-06 \tabularnewline
Triangular & 1543338.74811474 & 1.11706856627938e-06 \tabularnewline
Biweight & 1529356.04766228 & 1.10781575212115e-06 \tabularnewline
Cosine & 1534016.9478131 & 1.10858154788731e-06 \tabularnewline
Optcosine & 1515373.34720981 & 1.10837336527179e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=280139&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]1538677.84796392[/C][C]1.11209593457469e-06[/C][/ROW]
[ROW][C]Epanechnikov[/C][C]1515373.34720981[/C][C]1.10782916438556e-06[/C][/ROW]
[ROW][C]Rectangular[/C][C]1515373.34720981[/C][C]1.14689268067045e-06[/C][/ROW]
[ROW][C]Triangular[/C][C]1543338.74811474[/C][C]1.11706856627938e-06[/C][/ROW]
[ROW][C]Biweight[/C][C]1529356.04766228[/C][C]1.10781575212115e-06[/C][/ROW]
[ROW][C]Cosine[/C][C]1534016.9478131[/C][C]1.10858154788731e-06[/C][/ROW]
[ROW][C]Optcosine[/C][C]1515373.34720981[/C][C]1.10837336527179e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=280139&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=280139&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Maximum Density Values
Kernelx-valuemax. density
Gaussian1538677.847963921.11209593457469e-06
Epanechnikov1515373.347209811.10782916438556e-06
Rectangular1515373.347209811.14689268067045e-06
Triangular1543338.748114741.11706856627938e-06
Biweight1529356.047662281.10781575212115e-06
Cosine1534016.94781311.10858154788731e-06
Optcosine1515373.347209811.10837336527179e-06


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = no ; par3 = 512 ;
Parameters (R input):
par1 = 0 ; par2 = no ; par3 = 512 ;
R code (references can be found in the software module):
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()
mydensity1
bitmap(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')
}