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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, 18 Dec 2017 15:03:37 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/18/t1513605883f6bd866mlo89sjw.htm/, Retrieved Tue, 14 May 2024 18:08:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310184, Retrieved Tue, 14 May 2024 18:08:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact58
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [] [2017-12-18 14:03:37] [f1ade19563a25eb31edff11eb9af1158] [Current]
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Dataseries X:
37,90
22,20
44,20
16,70
12,10
9,50
18,80
11,30
14,10
35,40
10,30
12,30
16,10
33,50
29,60
36,50
12,20
8,60
30,50
19,00
16,20
17,90
30,40
18,10
8,60
27,70
7,70
23,90
31,60
19,10
18,30
17,70
38,10
18,10
19,50
10,90
44,20
36,90
14,60
21,90
17,80
23,70
9,50
9,00
8,90
11,00
18,30
20,20
8,30
9,20
15,20
27,90
12,10
10,50
8,30
35,60
11,00
15,70
42,90
10,30
12,10
12,50
16,80
18,80
15,50
28,40
Dataseries Y:
13,40
4,30
9,20
7,50
7,30
9,60
5,40
9,70
6,70
9,60
8,70
7,80
5,50
9,60
4,60
7,70
9,30
11,70
7,00
7,30
6,50
5,30
3,80
5,20
10,40
9,40
9,80
6,70
6,50
5,10
5,30
4,90
11,60
7,40
5,60
8,90
11,80
12,40
9,30
6,30
6,10
6,10
10,40
11,10
12,00
13,50
3,40
9,40
6,00
9,10
6,20
7,30
9,40
8,30
7,40
7,60
8,00
6,00
10,20
14,40
9,40
8,20
5,30
5,30
5,90
6,00




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310184&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=310184&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310184&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center







Bandwidth
x axis3.09053041730339
y axis1.03049266861185
Correlation
correlation used in KDE0.0231834489239366
correlation(x,y)0.0231834489239366

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.09053041730339 \tabularnewline
y axis & 1.03049266861185 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.0231834489239366 \tabularnewline
correlation(x,y) & 0.0231834489239366 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310184&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.09053041730339[/C][/ROW]
[ROW][C]y axis[/C][C]1.03049266861185[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.0231834489239366[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.0231834489239366[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310184&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310184&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 axis3.09053041730339
y axis1.03049266861185
Correlation
correlation used in KDE0.0231834489239366
correlation(x,y)0.0231834489239366



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')