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Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationSat, 03 Nov 2007 02:42:33 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/03/iwezp9doy8lqvcu1194082892.htm/, Retrieved Sun, 05 May 2024 08:05:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=215, Retrieved Sun, 05 May 2024 08:05:32 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [Various EDA topic...] [2007-11-03 09:42:33] [77c9c0d97755c69877fabe95ec1f485a] [Current]
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Dataseries X:
91,25
91,5
91,68
91,81
91,84
91,93
92,08
92,11
92,26
92,28
92,39
92,46
92,82
93,16
93,33
93,51
93,56
93,67
93,76
93,88
94,01
94,21
94,31
94,4
94,9
95,31
95,52
95,68
95,91
95,97
96,15
96,34
96,42
96,54
96,72
96,81
97,19
97,5
97,71
97,86
98,04
98,2
98,25
98,41
98,56
98,62
98,75
98,71
99,05
99,52
99,71
99,8
100,01
99,99
100,12
100,15
100,27
100,42
100,43
100,5
100,95
101,26
101,42
101,68
101,75
101,89
102,07
102,22
102,45
102,62
102,67
102,86
104,78
104,87
105,06
105,14
105,32
105,54
105,68
105,77
106,07
106,03
106,13
106,28
106,61
106,74
107,01
107,1
107,28
107,4
107,59
107,69
107,78
Dataseries Y:
1,79
1,95
2,26
2,04
2,16
2,75
2,79
2,88
3,36
2,97
3,1
2,49
2,2
2,25
2,09
2,79
3,14
2,93
2,65
2,67
2,26
2,35
2,13
2,18
2,9
2,63
2,67
1,81
1,33
0,88
1,28
1,26
1,26
1,29
1,1
1,37
1,21
1,74
1,76
1,48
1,04
1,62
1,49
1,79
1,8
1,58
1,86
1,74
1,59
1,26
1,13
1,92
2,61
2,26
2,41
2,26
2,03
2,86
2,55
2,27
2,26
2,57
3,07
2,76
2,51
2,87
3,14
3,11
3,16
2,47
2,57
2,89
2,63
2,38
1,69
1,96
2,19
1,87
1,6
1,63
1,22
1,21
1,49
1,64
1,66
1,77
1,82
1,78
1,28
1,29
1,37
1,12
1,51




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=215&T=0

[TABLE]
[ROW][C]Summary of compuational 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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=215&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=215&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis1.66684088947042
y axis0.264810067412221
Correlation
correlation used in KDE-0.293089385926140
correlation(x,y)-0.293089385926140

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.66684088947042 \tabularnewline
y axis & 0.264810067412221 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.293089385926140 \tabularnewline
correlation(x,y) & -0.293089385926140 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=215&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.66684088947042[/C][/ROW]
[ROW][C]y axis[/C][C]0.264810067412221[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.293089385926140[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.293089385926140[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=215&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=215&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 axis1.66684088947042
y axis0.264810067412221
Correlation
correlation used in KDE-0.293089385926140
correlation(x,y)-0.293089385926140



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')