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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 computationTue, 10 Nov 2009 07:00:53 -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/Nov/10/t1257861739rvj894ub6kje2jo.htm/, Retrieved Sun, 05 May 2024 21:19:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55236, Retrieved Sun, 05 May 2024 21:19:05 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Box-Cox Linearity Plot] [3/11/2009] [2009-11-02 21:47:57] [b98453cac15ba1066b407e146608df68]
- RMPD    [Bivariate Kernel Density Estimation] [ws2] [2009-11-10 14:00:53] [94ba0ef70f5b330d175ff4daa1c9cd40] [Current]
-   PD      [Bivariate Kernel Density Estimation] [ws2] [2009-11-12 13:55:20] [ca30429b07824e7c5d48293114d35d71]
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Dataseries X:
100.00
108.16
114.02
102.19
110.37
96.86
94.19
99.52
94.06
97.55
78.15
81.24
92.36
96.06
114.05
110.66
104.92
90.00
95.70
86.03
84.85
100.04
80.92
74.07
77.30
97.23
90.76
100.56
92.01
99.24
105.87
90.99
93.31
91.17
77.33
91.13
85.01
83.90
104.86
110.90
95.44
111.62
108.89
96.18
101.97
99.12
86.78
118.42
118.74
106.53
134.78
104.68
105.30
139.41
103.61
99.78
103.46
120.06
96.71
107.13
105.36
111.69
132.05
126.80
154.48
141.56
109.95
127.90
133.09
120.08
117.56
143.04
Dataseries Y:
100.00
99.97
101.03
101.00
101.30
101.43
101.49
102.14
102.58
102.34
102.07
101.83
102.14
102.58
102.63
102.74
103.32
103.27
102.48
102.14
102.07
101.69
101.15
100.90
101.77
101.93
102.27
102.49
102.80
102.82
102.83
102.89
102.87
102.67
102.96
103.22
103.53
104.63
104.63
104.17
103.93
104.01
104.16
105.22
105.85
106.21
105.77
105.63
106.49
107.51
110.43
111.42
111.58
111.34
111.08
111.66
112.36
112.31
111.52
110.87
111.13
112.71
113.25
113.09
112.55
112.87
113.59
115.14
116.38
116.50
116.25
116.73




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55236&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55236&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'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis6.20396078105513
y axis1.05336646960894
Correlation
correlation used in KDE0.682723266272451
correlation(x,y)0.682723266272451

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 6.20396078105513 \tabularnewline
y axis & 1.05336646960894 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.682723266272451 \tabularnewline
correlation(x,y) & 0.682723266272451 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55236&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]6.20396078105513[/C][/ROW]
[ROW][C]y axis[/C][C]1.05336646960894[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.682723266272451[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.682723266272451[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55236&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 axis6.20396078105513
y axis1.05336646960894
Correlation
correlation used in KDE0.682723266272451
correlation(x,y)0.682723266272451



Parameters (Session):
par1 = red ; par2 = blue ; par3 = TRUE ; par4 = BV ; par5 = BN ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; 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')