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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, 23 Jan 2017 10:36:40 +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/Jan/23/t14851642140x00exsiyaddeu7.htm/, Retrieved Fri, 01 Nov 2024 00:01:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=304496, Retrieved Fri, 01 Nov 2024 00:01:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [] [2017-01-23 09:36:40] [d42b2dfaed369a60e2334709a5cede2f] [Current]
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Dataseries X:
4
5
4
3
4
3
3
3
4
4
4
4
4
3
4
3
3
NA
5
4
3
4
4
4
4
3
3
4
2
5
4
4
5
4
2
4
3
4
4
4
5
4
3
5
5
4
4
3
4
2
4
5
5
4
4
4
3
3
4
4
5
2
4
3
4
4
4
4
5
3
3
4
4
4
4
3
4
3
3
4
4
3
4
4
4
5
5
4
3
3
4
4
4
4
4
3
4
5
5
4
3
5
4
5
3
5
4
4
4
4
3
4
4
3
4
3
4
5
5
4
4
3
4
4
4
3
4
4
3
4
3
4
5
2
3
4
5
NA
4
5
4
4
3
4
4
4
4
5
4
4
3
4
4
4
3
4
5
4
2
4
4
4
4
5
5
3
4
4
2
Dataseries Y:
2
3
4
4
4
4
4
4
5
5
4
4
4
3
4
4
4
NA
5
4
4
4
4
4
4
4
4
4
4
4
3
5
4
3
3
5
4
3
3
4
4
5
3
5
4
4
4
5
4
3
5
5
5
3
3
4
4
4
4
4
5
4
4
4
4
2
4
4
4
4
4
5
4
4
4
4
4
4
3
3
4
3
4
4
4
4
4
4
4
NA
2
4
4
4
5
4
4
4
4
5
4
3
4
4
4
4
4
4
4
4
4
4
4
3
4
4
4
4
4
4
4
4
4
4
5
4
4
4
4
4
2
4
4
4
3
4
5
NA
5
5
5
4
4
4
4
4
4
4
3
4
3
5
4
4
4
4
4
4
3
4
3
4
5
4
4
3
4
4
3




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=304496&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=304496&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304496&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 axis20
y axis20
Correlation
correlation used in KDE0.280942616276731
correlation(x,y)0.280942616276731

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 20 \tabularnewline
y axis & 20 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.280942616276731 \tabularnewline
correlation(x,y) & 0.280942616276731 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=304496&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]20[/C][/ROW]
[ROW][C]y axis[/C][C]20[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.280942616276731[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.280942616276731[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=304496&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=304496&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 axis20
y axis20
Correlation
correlation used in KDE0.280942616276731
correlation(x,y)0.280942616276731



Parameters (Session):
par1 = Score ; par2 = X1 ; par3 = Groep ; par4 = FALSE ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 20 ; par4 = 20 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
R code (references can be found in the software module):
par8 <- 'terrain.colors'
par7 <- 'Y'
par6 <- 'Y'
par5 <- '0'
par4 <- '0'
par3 <- '0'
par2 <- '50'
par1 <- '50'
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')