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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationMon, 14 Dec 2009 12:04:37 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Dec/14/t12608175297i01b6y4b2buez3.htm/, Retrieved Sun, 05 May 2024 17:25:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67624, Retrieved Sun, 05 May 2024 17:25:15 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Kernel Densityplot] [2009-11-17 17:28:18] [e3ea405fd32c91e274ac69cd329cf610]
- R PD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2009-12-14 19:04:37] [d1818fb1d9a1b0f34f8553ada228d3d5] [Current]
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Dataseries X:
107.11
107.57
107.81
108.75
109.43
109.62
109.54
109.53
109.84
109.67
109.79
109.56
110.22
110.40
110.69
110.72
110.89
110.58
110.94
110.91
111.22
111.09
111.00
111.06
111.55
112.32
112.64
112.36
112.04
112.37
112.59
112.89
113.22
112.85
113.06
112.99
113.32
113.74
113.91
114.52
114.96
114.91
115.30
115.44
115.52
116.08
115.94
115.56
115.88
116.66
117.41
117.68
117.85
118.21
118.92
119.03
119.17
118.95
118.92
118.90
Dataseries Y:
107.56
107.70
107.67
107.67
107.72
108.35
108.25
108.26
108.31
108.33
108.36
108.36
108.97
109.62
109.60
109.64
109.65
109.64
109.93
109.81
109.77
110.10
110.40
110.50
111.89
112.10
111.92
112.15
112.16
112.17
112.32
112.38
112.34
113.14
113.18
113.21
113.76
113.99
113.95
113.93
114.01
114.10
114.11
114.10
114.12
114.68
114.71
114.73
115.81
116.01
116.12
116.49
116.51
116.60
117.01
117.01
117.12
117.22
118.38
118.80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67624&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67624&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67624&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis1.38087620835877
y axis1.19793704737702
Correlation
correlation used in KDE0.979626993332084
correlation(x,y)0.979626993332084

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.38087620835877 \tabularnewline
y axis & 1.19793704737702 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.979626993332084 \tabularnewline
correlation(x,y) & 0.979626993332084 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67624&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.38087620835877[/C][/ROW]
[ROW][C]y axis[/C][C]1.19793704737702[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.979626993332084[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.979626993332084[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67624&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67624&T=1

As an alternative you can also use a QR Code:  

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

Bandwidth
x axis1.38087620835877
y axis1.19793704737702
Correlation
correlation used in KDE0.979626993332084
correlation(x,y)0.979626993332084



Parameters (Session):
par1 = 75 ; par2 = 75 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 75 ; par2 = 75 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
R code (references can be found in the software module):
par1 <- as(par1,'numeric')
par2 <- as(par2,'numeric')
par3 <- as(par3,'numeric')
par4 <- as(par4,'numeric')
par5 <- as(par5,'numeric')
library('GenKern')
if (par3==0) par3 <- dpik(x)
if (par4==0) par4 <- dpik(y)
if (par5==0) par5 <- cor(x,y)
if (par1 > 500) par1 <- 500
if (par2 > 500) par2 <- 500
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par7=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Bandwidth',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'x axis',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'y axis',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Correlation',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation used in KDE',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'correlation(x,y)',header=TRUE)
a<-table.element(a,cor(x,y))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')