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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 computationThu, 17 Dec 2009 02:44:13 -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/17/t12610431099a57eqiprkst1mh.htm/, Retrieved Tue, 30 Apr 2024 06:35:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68670, Retrieved Tue, 30 Apr 2024 06:35:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW Paper: Bivariate Kernel density
Estimated Impact138
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [WS 4 - Deel 1 - V...] [2009-10-26 08:28:42] [b103a1dc147def8132c7f643ad8c8f84]
- RMP     [Bivariate Kernel Density Estimation] [WS 4 - Deel 1 - V...] [2009-10-27 11:16:07] [b103a1dc147def8132c7f643ad8c8f84]
-  M D        [Bivariate Kernel Density Estimation] [Paper: Bivariate ...] [2009-12-17 09:44:13] [a45cc820faa25ce30779915639528ec2] [Current]
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Dataseries X:
-0.8
-0.2
0.2
1
0
-0.2
1
0.4
1
1.7
3.1
3.3
3.1
3.5
6
5.7
4.7
4.2
3.6
4.4
2.5
-0.6
-1.9
-1.9
0.7
-0.9
-1.7
-3.1
-2.1
0.2
1.2
3.8
4
6.6
5.3
7.6
4.7
6.6
4.4
4.6
6
4.8
4
2.7
3
4.1
4
2.7
2.6
3.1
4.4
3
2
1.3
1.5
1.3
3.2
1.8
3.3
1
2.4
0.4
-0.1
1.3
-1.1
-4.4
-7.5
-12.2
-14.5
-16
-16.7
-16.3
-16.9
Dataseries Y:
15,5
15,1
11,7
16,3
16,7
15
14,9
14,6
15,3
17,9
16,4
15,4
17,9
15,9
13,9
17,8
17,9
17,4
16,7
16
16,6
19,1
17,8
17,2
18,6
16,3
15,1
19,2
17,7
19,1
18
17,5
17,8
21,1
17,2
19,4
19,8
17,6
16,2
19,5
19,9
20
17,3
18,9
18,6
21,4
18,6
19,8
20,8
19,6
17,7
19,8
22,2
20,7
17,9
20,9
21,2
21,4
23
21,3
23,9
22,4
18,3
22,8
22,3
17,8
16,4
16
16,4
17,7
16,6
16,2
18,3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68670&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]1 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=68670&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68670&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis1.27972187176691
y axis1.03242281865842
Correlation
correlation used in KDE0.205467307966266
correlation(x,y)0.205467307966266

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.27972187176691 \tabularnewline
y axis & 1.03242281865842 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.205467307966266 \tabularnewline
correlation(x,y) & 0.205467307966266 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68670&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.27972187176691[/C][/ROW]
[ROW][C]y axis[/C][C]1.03242281865842[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.205467307966266[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.205467307966266[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68670&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68670&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 axis1.27972187176691
y axis1.03242281865842
Correlation
correlation used in KDE0.205467307966266
correlation(x,y)0.205467307966266



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')