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Description of Statistical Computation

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 computationMon, 27 Oct 2014 14:14:01 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Oct/27/t1414419258qjna2io8d4rz8sy.htm/, Retrieved Fri, 10 May 2024 02:02:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=247042, Retrieved Fri, 10 May 2024 02:02:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact65

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Care Age 10 Data] [2009-10-26 09:01:50] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Boxplot and Trimmed Means] [Care Age 7 Data] [2009-10-26 18:36:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P     [CARE Data - Boxplots and Scatterplot Matrix] [CARE Data] [2010-10-19 14:16:27] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [CARE Data - Boxplots and Scatterplot Matrix] [CARE data - works...] [2011-10-17 10:23:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP         [Boxplot and Trimmed Means] [CARE Study Age 7 ] [2013-10-17 12:59:45] [34296d8f7657c52ed60d5bff9133afec]
- RM            [Boxplot and Trimmed Means] [year 7 data] [2014-10-23 10:48:16] [770cabeb704b463c26ebb6813270a402]
-  M D            [Boxplot and Trimmed Means] [Year 10data] [2014-10-27 13:53:03] [770cabeb704b463c26ebb6813270a402]
-    D              [Boxplot and Trimmed Means] [AFS] [2014-10-27 14:05:09] [770cabeb704b463c26ebb6813270a402]
- RM                  [Kernel Density Estimation] [Maternal IQ] [2014-10-27 14:09:12] [770cabeb704b463c26ebb6813270a402]
- R  D                  [Kernel Density Estimation] [AVA] [2014-10-27 14:11:46] [770cabeb704b463c26ebb6813270a402]
-    D                      [Kernel Density Estimation] [ARD] [2014-10-27 14:14:01] [f06adca6bfb99da24b496db9458d00d0] [Current]
-    D                        [Kernel Density Estimation] [AMA] [2014-10-27 14:15:17] [770cabeb704b463c26ebb6813270a402]
-    D                          [Kernel Density Estimation] [AKN] [2014-10-27 14:16:29] [770cabeb704b463c26ebb6813270a402]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95
87
91
84
92
84
84
69
84
84
85
89
83
86
91
90
77
88
88
88
102
103
84
87
88
93
101
88
113
95
99
85
105
105
96
88
93
93
69
83
83
93
69
86
90
87
92
75
89
88
87
113
102
101
87
105
101
79
86
95
104
79
86
81
92
95
97
87
94
105
94
88
105
113
69
69
100
113
88
104
94
91
103
95
69
86
108
83
102
94
113
113
93
105
88
90
92
81
86
85
86
97
103
102

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'Sir Ronald Aylmer Fisher' @ fisher.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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247042&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247042&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247042&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Properties of Density Trace
Bandwidth3.51517476213255
#Observations104

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 3.51517476213255 \tabularnewline
#Observations & 104 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247042&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]3.51517476213255[/C][/ROW]
[ROW][C]#Observations[/C][C]104[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247042&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247042&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
Bandwidth3.51517476213255
#Observations104






Maximum Density Values
Kernelx-valuemax. density
Gaussian87.75181655850040.0448232209147611
Epanechnikov88.51609501532390.0445685239953299
Rectangular89.02561398653950.047647938122789
Triangular88.00657604410820.045085935095174
Biweight88.51609501532390.0444145975693971
Cosine88.2613355297160.0444072493673049
Optcosine88.51609501532390.0445128247217212

\begin{tabular}{lllllllll}
\hline
Maximum Density Values \tabularnewline
Kernel & x-value & max. density \tabularnewline
Gaussian & 87.7518165585004 & 0.0448232209147611 \tabularnewline
Epanechnikov & 88.5160950153239 & 0.0445685239953299 \tabularnewline
Rectangular & 89.0256139865395 & 0.047647938122789 \tabularnewline
Triangular & 88.0065760441082 & 0.045085935095174 \tabularnewline
Biweight & 88.5160950153239 & 0.0444145975693971 \tabularnewline
Cosine & 88.261335529716 & 0.0444072493673049 \tabularnewline
Optcosine & 88.5160950153239 & 0.0445128247217212 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247042&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]87.7518165585004[/C][C]0.0448232209147611[/C][/ROW]
[ROW][C]Epanechnikov[/C][C]88.5160950153239[/C][C]0.0445685239953299[/C][/ROW]
[ROW][C]Rectangular[/C][C]89.0256139865395[/C][C]0.047647938122789[/C][/ROW]
[ROW][C]Triangular[/C][C]88.0065760441082[/C][C]0.045085935095174[/C][/ROW]
[ROW][C]Biweight[/C][C]88.5160950153239[/C][C]0.0444145975693971[/C][/ROW]
[ROW][C]Cosine[/C][C]88.261335529716[/C][C]0.0444072493673049[/C][/ROW]
[ROW][C]Optcosine[/C][C]88.5160950153239[/C][C]0.0445128247217212[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247042&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247042&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
Gaussian87.75181655850040.0448232209147611
Epanechnikov88.51609501532390.0445685239953299
Rectangular89.02561398653950.047647938122789
Triangular88.00657604410820.045085935095174
Biweight88.51609501532390.0444145975693971
Cosine88.2613355297160.0444072493673049
Optcosine88.51609501532390.0445128247217212


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = TRUE ; par3 = 5 ;
Parameters (R input):
par1 = 2 ; par2 = TRUE ; par3 = 5 ;
R code (references can be found in the software module):
par3 <- '512'
par2 <- 'no'
par1 <- '0'
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')
}