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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, 18 Dec 2014 16:46:45 +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/18/t1418921268hyw4mrkdczgfrex.htm/, Retrieved Sun, 19 May 2024 19:51:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271132, Retrieved Sun, 19 May 2024 19:51:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact68
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bootstrap Plot - Central Tendency] [bootstrap plot] [2014-12-15 10:33:55] [7b9119a46b6eb1a22eecca7bc054a6e2]
- RMPD    [Bivariate Kernel Density Estimation] [] [2014-12-18 16:46:45] [88f8137dd67cdcd531568536dca46410] [Current]
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Dataseries X:
21
22
21
21
21
21
21
23
22
25
21
23
22
21
21
25
21
21
20
24
23
21
24
23
21
22
20
18
21
22
22
21
21
25
22
22
20
21
21
21
22
21
24
22
22
21
22
19
22
23
20
20
23
20
23
21
22
21
21
19
22
21
21
21
21
21
21
22
22
18
21
23
19
19
21
21
21
20
19
21
19
19
19
20
19
19
19
20
19
18
19
21
18
18
19
21
20
24
22
21
21
19
19
20
18
19
19
20
21
18
19
19
22
22
22
20
19
20
22
21
21
21
21
21
21
21
22
24
21
22
20
21
24
25
22
21
21
22
23
24
20
22
25
22
21
21
21
22
22
21
22
23
21
21
21
19
21
21
19
18
19
21
22
22
19
20
19
21
19
20
21
19
21
21
21
19
25
21
20
25
19
20
22
19
20
19
19
18
19
21
19
20
20
19
19
22
21
19
19
19
23
19
20
19
22
19
25
19
19
19
20
20
21
19
21
23
19
22
20
18
21
20
21
21
21
19
21
19
21
21
22
21
22
22
22
22
21
22
23
19
22
21
19
19
20
18
21
21
20
20
21
21
19
19
21
19
19
24
19
19
20
19
19
19
19
19
19
20
20
19
21
19
19
19
21
22
19
19
Dataseries Y:
12
8
11
13
11
10
7
10
15
12
12
10
10
14
6
12
14
11
8
12
15
13
11
12
7
11
7
12
12
13
9
11
12
15
12
6
5
13
11
6
12
10
6
12
11
6
12
12
8
10
11
7
12
13
14
12
6
14
10
12
11
10
7
12
7
12
12
10
10
12
12
12
8
10
5
10
12
11
9
12
11
10
12
10
9
11
12
7
11
12
6
9
15
10
11
12
12
12
11
9
11
12
12
14
8
10
9
10
9
10
12
11
9
11
12
12
7
12
12
12
10
15
10
15
10
15
9
15
12
13
12
12
8
9
15
12
12
15
11
12
6
14
12
12
12
11
12
12
12
12
8
8
12
12
11
10
11
12
13
12
12
10
10
11
8
12
9
12
9
11
15
8
8
11
11
11
13
7
12
8
8
4
11
10
7
12
11
9
10
8
8
11
12
10
10
12
8
11
8
10
14
9
9
10
13
12
13
8
3
8
12
11
9
12
12
12
10
13
9
12
11
14
11
9
12
8
15
12
14
12
9
9
13
13
15
11
7
10
11
14
14
13
12
8
13
9
12
13
11
11
13
12
12
10
9
10
13
13
9
11
12
8
12
12
12
9
12
12
11
12
6
7
10
12
10
12
9
3




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' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271132&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' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271132&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271132&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' @ yule.wessa.net







Bandwidth
x axis0.233977222491268
y axis0.410311007963788
Correlation
correlation used in KDE0.191783482472292
correlation(x,y)0.191783482472292

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.233977222491268 \tabularnewline
y axis & 0.410311007963788 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.191783482472292 \tabularnewline
correlation(x,y) & 0.191783482472292 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271132&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.233977222491268[/C][/ROW]
[ROW][C]y axis[/C][C]0.410311007963788[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.191783482472292[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.191783482472292[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271132&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271132&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 axis0.233977222491268
y axis0.410311007963788
Correlation
correlation used in KDE0.191783482472292
correlation(x,y)0.191783482472292



Parameters (Session):
par1 = 0 ; par2 = 0 ;
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')