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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, 07 Dec 2010 10:03:14 +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/Dec/07/t1291716073zdvldna3cp6r6he.htm/, Retrieved Fri, 03 May 2024 18:48:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=106111, Retrieved Fri, 03 May 2024 18:48:08 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact121
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [ARIMA Forecasting] [WS9 fout] [2010-12-03 12:26:23] [1fd136673b2a4fecb5c545b9b4a05d64]
- R P   [ARIMA Forecasting] [] [2010-12-03 14:12:57] [b98453cac15ba1066b407e146608df68]
F   P     [ARIMA Forecasting] [WS9: ARIMA foreca...] [2010-12-03 14:39:04] [1fd136673b2a4fecb5c545b9b4a05d64]
- RMPD      [Bivariate Kernel Density Estimation] [Paper: Bivariate ...] [2010-12-05 16:09:57] [1fd136673b2a4fecb5c545b9b4a05d64]
-   PD          [Bivariate Kernel Density Estimation] [Paper: B. Kernel ...] [2010-12-07 10:03:14] [380f6bceef280be3d93cc6fafd18141e] [Current]
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Dataseries X:
24
25
30
19
22
22
25
23
17
21
19
19
15
16
23
27
22
14
22
23
23
21
19
18
20
23
25
19
24
22
25
26
29
32
25
29
28
17
28
29
26
25
14
25
26
20
18
32
25
25
23
21
20
15
30
24
26
24
22
14
24
24
24
24
19
31
22
27
19
25
20
21
27
23
25
20
21
22
23
25
25
17
19
25
19
20
26
23
27
17
17
19
17
22
21
32
21
21
18
18
23
19
20
21
20
17
18
19
22
15
14
18
24
35
29
21
25
20
22
13
26
17
25
20
19
21
22
24
21
26
24
16
23
18
16
26
19
21
21
22
23
29
21
21
23
27
25
21
10
20
26
24
29
19
24
19
24
22
17
Dataseries Y:
26
23
25
23
19
29
25
21
22
25
24
18
22
15
22
28
20
12
24
20
21
20
21
23
28
24
24
24
23
23
29
24
18
25
21
26
22
22
22
23
30
23
17
23
23
25
24
24
23
21
24
24
28
16
20
29
27
22
28
16
25
24
28
24
23
30
24
21
25
25
22
23
26
23
25
21
25
24
29
22
27
26
22
24
27
24
24
29
22
21
24
24
23
20
27
26
25
21
21
19
21
21
16
22
29
15
17
15
21
21
19
24
20
17
23
24
14
19
24
13
22
16
19
25
25
23
24
26
26
25
18
21
26
23
23
22
20
13
24
15
14
22
10
24
22
24
19
20
13
20
22
24
29
12
20
21
24
22
20




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=106111&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=106111&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106111&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 axis1.60452767208203
y axis0.899293623123179
Correlation
correlation used in KDE0.352190108955845
correlation(x,y)0.352190108955845

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.60452767208203 \tabularnewline
y axis & 0.899293623123179 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.352190108955845 \tabularnewline
correlation(x,y) & 0.352190108955845 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=106111&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.60452767208203[/C][/ROW]
[ROW][C]y axis[/C][C]0.899293623123179[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.352190108955845[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.352190108955845[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=106111&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=106111&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 axis1.60452767208203
y axis0.899293623123179
Correlation
correlation used in KDE0.352190108955845
correlation(x,y)0.352190108955845



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')