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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 computationWed, 16 Nov 2011 05:11:37 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/16/t1321438309e2tpl1gvgrcj0ie.htm/, Retrieved Thu, 28 Mar 2024 09:47:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=143769, Retrieved Thu, 28 Mar 2024 09:47:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact104
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Pearson Correlation] [Screen dimensions] [2010-09-25 10:10:17] [b98453cac15ba1066b407e146608df68]
- RMP   [Bivariate Kernel Density Estimation] [Paper] [2011-11-14 20:01:53] [fbaf17a8836493f6de0f4e0e997711e1]
- R P       [Bivariate Kernel Density Estimation] [] [2011-11-16 10:11:37] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
1280
1024
1120
1024
1280
1280
1280
1024
1280
1280
1280
1280
1280
1688
1440
1600
1280
1280
1280
1176
1280
1503
1440
1366
1280
1024
1280
2560
1280
1024
1280
1280
1440
1280
1440
1024
1440
1143
1280
1440
1280
1366
1024
1408
1366
1176
1920
1257
1280
1280
1440
1680
1440
1024
1140
1280
1280
1280
1280
1280
1440
1280
1152
1280
1280
1440
1280
1280
1440
1280
1280
1440
1280
1280
1600
1024
1366
1280
1280
1440
1366
1280
1024
1280
1440
1280
1280
1408
1280
1600
1600
1680
1440
1440
917
1280
1760
1280
1280
1280
1024
1366
1440
1280
1280
1920
1024
1024
1600
1117
1440
983
1024
1024
1280
1440
1280
1280
1280
1440
1280
1024
1024
1152
1280
1024
1366
1680
1680
1280
1366
1024
1440
1024
1280
1280
1280
1024
1280
Dataseries Y:
1024
768
700
768
800
1024
800
768
800
1024
800
800
1024
949
900
1200
800
800
768
735
800
845
900
768
768
768
800
1440
768
768
1024
800
900
800
900
768
900
857
800
900
800
768
768
880
768
735
1200
785
800
800
900
1050
900
768
641
1024
800
800
800
800
900
800
864
1024
800
900
800
1024
900
800
800
900
800
1024
900
768
768
800
800
900
768
800
768
800
900
800
800
880
800
900
900
1050
900
900
550
800
990
800
800
800
768
768
900
800
1024
1080
768
768
900
698
900
737
768
640
800
900
800
800
800
900
800
768
768
864
768
768
768
1050
1050
800
768
768
900
768
800
800
800
768
800




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 6 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=143769&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=143769&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=143769&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 time6 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net







Bandwidth
x axis17.2930035186097
y axis15.1116423026101
Correlation
correlation used in KDE0.767558899807277
correlation(x,y)0.767558899807277

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 17.2930035186097 \tabularnewline
y axis & 15.1116423026101 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.767558899807277 \tabularnewline
correlation(x,y) & 0.767558899807277 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=143769&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]17.2930035186097[/C][/ROW]
[ROW][C]y axis[/C][C]15.1116423026101[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.767558899807277[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.767558899807277[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=143769&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=143769&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 axis17.2930035186097
y axis15.1116423026101
Correlation
correlation used in KDE0.767558899807277
correlation(x,y)0.767558899807277



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')
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')