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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, 15 Dec 2014 14:40:48 +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/2014/Dec/15/t141865455238cffjhfweysxo7.htm/, Retrieved Thu, 31 Oct 2024 23:09:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268524, Retrieved Thu, 31 Oct 2024 23:09:08 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact74
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [] [2014-12-15 14:40:48] [023a69c6c348bca0f1811b046758af62] [Current]
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Dataseries X:
15
20
21
8
19
22
12
22
12
22
10
22
24
18
22
20
19
11
8
15
18
18
19
30
27
18
28
27
28
21
22
20
23
18
18
25
25
25
24
13
17
4
16
21
20
22
0
18
29
15
22
22
17
27
15
26
18
27
17
19
13
16
2
26
22
18
21
24
17
20
21
21
16
15
21
18
22
23
22
20
27
20
21
26
18
16
20
18
16
10
23
23
19
17
26
20
24
20
16
22
19
15
12
15
18
18
12
28
21
30
14
18
19
25
23
17
21
29
20
23
24
20
23
17
21
20
20
19
26
23
24
21
21
8
17
20
19
17
24
20
25
20
21
22
25
28
29
20
20
19
19
26
10
17
30
22
23
16
18
25
18
24
23
24
15
20
26
23
23
22
15
22
10
20
23
27
23
25
20
24
19
24
19
21
27
20
17
21
18
24
27
20
25
21
25
20
27
18
26
18
21
18
25
20
23
22
18
25
22
14
26
15
21
20
22
20
26
20
15
25
20
27
17
22
24
22
23
20
22
27
24
25
19
24
22
18
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Dataseries Y:
21
26
22
20
19
18
21
15
21
16
16
19
10
26
23
16
23
21
19
18
25
19
14
16
20
23
18
18
19
22
14
23
20
13
16
7
17
19
23
19
16
20
25
17
12
24
14
18
19
16
19
4
20
24
17
22
19
22
23
23
24
7
19
19
16
19
24
16
16
26
18
19
19
16
16
16
20
15
22
16
11
16
15
16
18
25
22
17
22
23
13
19
15
20
15
20
13
24
20
22
26
25
23
14
24
13
23
22
26
16
11
19
25
19
22
14
22
18
23
12
22
21
19
22
15
20
20
16
23
18
25
9
23
25
25
18
23
21
22
23
23
24
24
15
19
18
27
13
28
19
19
17
26
28
24
23
22
21
25
27
23
23
19
15
20
16
25
25
19
16
19
19
23
21
19
20
3
23
15
24
24
24
28
23
25
25
20
25
23
20
16
23
11
23
29
16
23
20
4
24
16
3
23
20
19
24
27
22
17
23
28
29
21
20
28
26
20
23
24
21
16
21
28
23
29
18
22
14
15
15
20
21
17
20
24
28
20
27
22
24
18
19
23
23
19
25
24
27
16
15
27
21
16
22
17
23
14
24
21
16
19
16
11
23
27
23
24
22
26
19
19
20
16
22
21
26
23
21
26
27
17
22
19
20
26




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268524&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268524&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268524&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'Gertrude Mary Cox' @ cox.wessa.net







Bandwidth
x axis1.4629202308863
y axis1.46855663206447
Correlation
correlation used in KDE-0.0604597217657167
correlation(x,y)-0.0604597217657167

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.4629202308863 \tabularnewline
y axis & 1.46855663206447 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.0604597217657167 \tabularnewline
correlation(x,y) & -0.0604597217657167 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268524&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.4629202308863[/C][/ROW]
[ROW][C]y axis[/C][C]1.46855663206447[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.0604597217657167[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.0604597217657167[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268524&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268524&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 axis1.4629202308863
y axis1.46855663206447
Correlation
correlation used in KDE-0.0604597217657167
correlation(x,y)-0.0604597217657167



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
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')
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
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
if (par8 == 'terrain.colors') mycol <- terrain.colors(100)
if (par8 == 'rainbow') mycol <- rainbow(100)
if (par8 == 'heat.colors') mycol <- heat.colors(100)
if (par8 == 'topo.colors') mycol <- topo.colors(100)
if (par8 == 'cm.colors') mycol <- cm.colors(100)
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$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')