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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 19:15:12 +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/t1418670950k8d0adeuqbkphms.htm/, Retrieved Thu, 16 May 2024 20:06:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268933, Retrieved Thu, 16 May 2024 20:06:26 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2014-12-15 19:15:12] [ca907db95fc0b179b22bb0898c34dff4] [Current]
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Dataseries X:
30
17
24
20
25
20
27
18
28
21
27
22
28
25
21
22
28
20
29
20
20
23
18
18
19
25
25
25
24
19
26
10
17
13
17
30
4
16
21
22
20
22
23
16
0
18
25
18
18
24
29
15
22
23
24
22
15
17
20
27
26
23
23
15
26
22
18
15
22
27
10
20
17
23
19
13
27
23
16
25
2
26
20
22
24
23
22
21
25
27
23
23
18
18
23
19
15
20
16
25
25
19
19
16
19
19
23
21
22
19
20
3
23
14
23
20
15
13
16
7
24
17
24
24
19
28
23
19
23
25
25
20
16
20
25
25
23
17
20
16
23
12
24
11
14
23
18
29
16
19
16
23
19
4
20
20
4
24
16
3
24
23
17
20
22
19
24
19
27
22
23
Dataseries Y:
26,56
20,16
30,24
18,56
23,36
22,16
23,76
18,8
29,52
25,44
31,84
17,52
29,52
24,16
24
18,16
25,52
28,96
23,36
28,16
24,56
21,44
22,24
24,4
20,64
25,76
27,76
21,04
19,44
20,16
16,56
24,64
15,36
29,12
21,76
23,76
22,56
23,84
26
21,76
25,04
23,36
20,24
19,04
30,72
26,56
17,92
21,12
25,36
17,84
25,04
12,24
24,32
24,96
20,96
18,96
19,84
18,24
23,84
31,84
17,92
23,36
23,6
24,24
26,96
12,56
20,16
12,56
17,52
19,76
15,92
23,84
26,64
21,44
22,32
25,12
26,96
17,52
24,56
19,52
24,16
28,4
24,32
26,64
12,96
6,96
20,32
28,96
28,56
27,36
30,56
25,76
21,36
29,44
23,52
16,96
20,16
25,92
21,76
22,56
23,2
25,84
23,6
23,68
19,92
20,24
27,76
13,76
29,44
25,76
28,4
24,4
28,24
24,96
26,16
28,24
21,76
18,72
22,96
23,6
29,2
15,84
25,6
29,2
26,96
30,32
24,96
27,36
25,76
24,64
24,64
21,36
30,56
12,16
30,56
23,6
30,8
21,76
20,4
15,76
24,4
19,04
26,16
19,84
22,96
29,04
28,4
19,76
24,96
30,88
27,36
29,44
30,48
29,68
30,56
20,56
15,2
7,2
21,76
18,72
21,36
28,4
28,16
22,48
25,76
21,36
18,96
19,12
21,12
12,32
23,36




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 2 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268933&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268933&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268933&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'Sir Maurice George Kendall' @ kendall.wessa.net







Bandwidth
x axis1.60312902964584
y axis1.69855921803013
Correlation
correlation used in KDE0.112013750398079
correlation(x,y)0.112013750398079

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.60312902964584 \tabularnewline
y axis & 1.69855921803013 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.112013750398079 \tabularnewline
correlation(x,y) & 0.112013750398079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268933&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.60312902964584[/C][/ROW]
[ROW][C]y axis[/C][C]1.69855921803013[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.112013750398079[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.112013750398079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268933&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268933&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 axis1.60312902964584
y axis1.69855921803013
Correlation
correlation used in KDE0.112013750398079
correlation(x,y)0.112013750398079



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')