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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 14:09:12 +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/t1414418982di6pt0oyc0z567q.htm/, Retrieved Fri, 10 May 2024 19:17:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=247033, Retrieved Fri, 10 May 2024 19:17:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact67

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] [f06adca6bfb99da24b496db9458d00d0] [Current]
- R  D                    [Kernel Density Estimation] [AVA] [2014-10-27 14:11:46] [770cabeb704b463c26ebb6813270a402]
-    D                      [Kernel Density Estimation] [ARD] [2014-10-27 14:14:01] [770cabeb704b463c26ebb6813270a402]
-    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 
88
98
89
81
88
95
79
91
80
91
85
94
86
82
107
97
78
91
74
95
97
112
80
98
102
100
97
92
114
88
96
91
114
91
114
89
103
83
74
88
88
98
74
86
93
85
91
75
97
88
79
106
102
98
98
114
95
98
82
97
94
84
88
83
98
106
94
91
89
102
103
96
89
112
74
74
102
106
91
94
98
85
108
90
74
81
104
90
95
85
114
114
93
104
92
100
92
77
86
87
91
102
100
113

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=247033&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=247033&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247033&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
Bandwidth3.31620260578542
#Observations104

\begin{tabular}{lllllllll}
\hline
Properties of Density Trace \tabularnewline
Bandwidth & 3.31620260578542 \tabularnewline
#Observations & 104 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247033&T=1

[TABLE]
[ROW][C]Properties of Density Trace[/C][/ROW]
[ROW][C]Bandwidth[/C][C]3.31620260578542[/C][/ROW]
[ROW][C]#Observations[/C][C]104[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247033&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247033&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
Bandwidth3.31620260578542
#Observations104






Maximum Density Values
Kernelx-valuemax. density
Gaussian91.36264706109390.0383634432771004
Epanechnikov91.94872549196190.0388655490186939
Rectangular92.53480392282990.0425241538203098
Triangular91.01100000257310.0389480198681177
Biweight92.18315686430910.0385651845519657
Cosine92.06594117813550.0384784846974524
Optcosine91.94872549196190.0387667125488042

\begin{tabular}{lllllllll}
\hline
Maximum Density Values \tabularnewline
Kernel & x-value & max. density \tabularnewline
Gaussian & 91.3626470610939 & 0.0383634432771004 \tabularnewline
Epanechnikov & 91.9487254919619 & 0.0388655490186939 \tabularnewline
Rectangular & 92.5348039228299 & 0.0425241538203098 \tabularnewline
Triangular & 91.0110000025731 & 0.0389480198681177 \tabularnewline
Biweight & 92.1831568643091 & 0.0385651845519657 \tabularnewline
Cosine & 92.0659411781355 & 0.0384784846974524 \tabularnewline
Optcosine & 91.9487254919619 & 0.0387667125488042 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=247033&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]91.3626470610939[/C][C]0.0383634432771004[/C][/ROW]
[ROW][C]Epanechnikov[/C][C]91.9487254919619[/C][C]0.0388655490186939[/C][/ROW]
[ROW][C]Rectangular[/C][C]92.5348039228299[/C][C]0.0425241538203098[/C][/ROW]
[ROW][C]Triangular[/C][C]91.0110000025731[/C][C]0.0389480198681177[/C][/ROW]
[ROW][C]Biweight[/C][C]92.1831568643091[/C][C]0.0385651845519657[/C][/ROW]
[ROW][C]Cosine[/C][C]92.0659411781355[/C][C]0.0384784846974524[/C][/ROW]
[ROW][C]Optcosine[/C][C]91.9487254919619[/C][C]0.0387667125488042[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=247033&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=247033&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
Gaussian91.36264706109390.0383634432771004
Epanechnikov91.94872549196190.0388655490186939
Rectangular92.53480392282990.0425241538203098
Triangular91.01100000257310.0389480198681177
Biweight92.18315686430910.0385651845519657
Cosine92.06594117813550.0384784846974524
Optcosine91.94872549196190.0387667125488042


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = TRUE ; par3 = 5 ;
Parameters (R input):
par1 = 0 ; par2 = no ; par3 = 512 ;
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')
}