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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 computationTue, 27 Oct 2009 14:49:43 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/27/t1256676614vuzv4v2zv9j5pzt.htm/, Retrieved Tue, 07 May 2024 14:54:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51236, Retrieved Tue, 07 May 2024 14:54:55 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [WS 4 model1] [2009-10-26 21:16:15] [830e13ac5e5ac1e5b21c6af0c149b21d]
- RMP     [Bivariate Kernel Density Estimation] [WS4 part 2] [2009-10-27 20:49:43] [51118f1042b56b16d340924f16263174] [Current]
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Dataseries X:
0.818465
0.800641
0.769764
0.745823
0.762253
0.768403
0.757518
0.772917
0.787774
0.82203
0.830772
0.813537
0.815927
0.832293
0.848464
0.843455
0.826241
0.837661
0.831947
0.81493
0.783085
0.790514
0.788395
0.780579
0.785731
0.792959
0.776337
0.75683
0.76929
0.764877
0.755173
0.739864
0.740138
0.745212
0.729076
0.734107
0.719632
0.702889
0.681013
0.686342
0.67944
0.678058
0.644039
0.63488
0.642797
0.642963
0.634115
0.66778
0.695894
0.750638
0.785423
0.74355
0.755344
0.782167
0.766284
0.75815
0.732601
0.71347
0.709824
0.700869
Dataseries Y:
1076.7
1035.9
1037
1154
1237.2
996.6
1238.2
1153.4
1268.1
1156
1144.5
1232.9
1055.2
1109.7
1079.8
1126.3
1196.8
1130.4
1183.6
1200.9
1426.6
1080.4
1325.4
1230
1125.9
1174.5
1151.9
1439.3
1344.3
1319.1
1257.6
1249.1
1397.1
1348
1548.2
1377.6
1402.9
1167.6
1392.9
1547
1420
1266.4
1280.8
1128.6
1449.5
1511.7
1548.3
1652
1650.5
1370.8
1653.3
1474.3
1418.8
1554.1
1156.6
1223.4
1337.5
1098.9
1037.6
1202.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51236&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51236&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51236&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis0.0233441014484868
y axis70.7298015103388
Correlation
correlation used in KDE-0.488221079599418
correlation(x,y)-0.488221079599418

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.0233441014484868 \tabularnewline
y axis & 70.7298015103388 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.488221079599418 \tabularnewline
correlation(x,y) & -0.488221079599418 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51236&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.0233441014484868[/C][/ROW]
[ROW][C]y axis[/C][C]70.7298015103388[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.488221079599418[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.488221079599418[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51236&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51236&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 axis0.0233441014484868
y axis70.7298015103388
Correlation
correlation used in KDE-0.488221079599418
correlation(x,y)-0.488221079599418



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
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
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$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')