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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 computationSun, 28 Nov 2010 16:32:46 +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/2010/Nov/28/t1290961888f3c6npk49upmjs9.htm/, Retrieved Thu, 02 May 2024 23:23:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=102643, Retrieved Thu, 02 May 2024 23:23:27 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Connected vs Sepa...] [2010-10-04 07:42:21] [b98453cac15ba1066b407e146608df68]
-    D    [Bivariate Kernel Density Estimation] [Popularity vs Kno...] [2010-11-28 16:32:46] [bff44ea937c3f909b1dc9a8bfab919e2] [Current]
-   PD      [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2010-11-28 16:40:22] [26379b86c25fbf0febe6a7a428e65173]
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Dataseries X:
13
12
15
12
10
12
15
9
12
11
11
11
15
7
11
11
10
14
10
6
11
15
11
12
14
15
9
13
13
16
13
12
14
11
9
16
12
10
13
16
14
15
5
8
11
16
17
9
9
13
10
6
12
8
14
12
11
16
8
15
7
16
14
16
9
14
11
13
15
5
15
13
11
11
12
12
12
12
14
6
7
14
14
10
13
12
9
12
16
10
14
10
16
15
12
10
8
8
11
13
16
16
14
11
4
14
9
14
8
8
11
12
11
14
15
16
16
11
14
14
12
14
8
13
16
12
16
12
11
4
16
15
10
13
15
12
14
7
19
12
12
13
15
8
12
10
8
10
15
16
13
16
9
14
14
12
Dataseries Y:
14
8
12
7
10
7
16
11
14
6
16
11
16
12
7
13
11
15
7
9
7
14
15
7
15
17
15
14
14
8
8
14
14
8
11
16
10
8
14
16
13
5
8
10
8
13
15
6
12
16
5
15
12
8
13
14
12
16
10
15
8
16
19
14
6
13
15
7
13
4
14
13
11
14
12
15
14
13
8
6
7
13
13
11
5
12
8
11
14
9
10
13
16
16
11
8
4
7
14
11
17
15
17
5
4
10
11
15
10
9
12
15
7
13
12
14
14
8
15
12
12
16
9
15
15
6
14
15
10
6
14
12
8
11
13
9
15
13
15
14
16
14
14
10
10
4
8
15
16
12
12
15
9
12
14
11




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102643&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102643&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102643&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'George Udny Yule' @ 72.249.76.132







Bandwidth
x axis1.02583037226533
y axis0.989825289755048
Correlation
correlation used in KDE0.583743856743056
correlation(x,y)0.583743856743056

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.02583037226533 \tabularnewline
y axis & 0.989825289755048 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.583743856743056 \tabularnewline
correlation(x,y) & 0.583743856743056 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=102643&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.02583037226533[/C][/ROW]
[ROW][C]y axis[/C][C]0.989825289755048[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.583743856743056[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.583743856743056[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=102643&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=102643&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 axis1.02583037226533
y axis0.989825289755048
Correlation
correlation used in KDE0.583743856743056
correlation(x,y)0.583743856743056



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
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')