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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 computationFri, 13 Nov 2009 12:29:06 -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/2009/Nov/13/t1258140598l12b1mt9xuuxle1.htm/, Retrieved Sun, 05 May 2024 09:01:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57038, Retrieved Sun, 05 May 2024 09:01:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact131
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [3/11/2009] [2009-11-02 21:54:51] [b98453cac15ba1066b407e146608df68]
- R PD  [Bivariate Kernel Density Estimation] [] [2009-11-11 15:32:10] [74be16979710d4c4e7c6647856088456]
-    D      [Bivariate Kernel Density Estimation] [] [2009-11-13 19:29:06] [f066b5fba39549422fd1c7a1f2ce0075] [Current]
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Dataseries X:
153,24
184,48
191,81
168,19
163,81
190,57
163,81
129,62
173,90
198,76
135,52
179,81
137,05
142,57
187,52
220,48
208,76
210,19
232,57
173,81
218,86
226,76
196,67
237,43
173,14
207,62
234,67
204,10
230,76
210,19
194,76
172,10
221,90
225,24
228,00
198,76
199,05
235,43
270,76
234,10
237,24
239,43
239,24
197,33
217,43
242,19
207,52
232,76
222,10
202,48
228,10
319,52
236,95
252,00
262,29
172,10
243,90
235,62
216,95
236,29
Dataseries Y:
146,54
120,13
131,67
131,97
145,92
177,02
149,56
171,58
173,95
190,39
183,46
165,44
186,32
223,29
198,99
191,05
178,42
187,85
183,51
252,94
213,51
185,53
215,48
214,39
229,21
183,55
206,71
186,23
217,46
214,69
202,06
225,57
220,70
246,32
273,51
220,66
295,88
215,35
230,83
220,00
232,06
237,68
294,39
295,35
267,68
274,12
246,84
249,34
303,25
236,14
233,38
260,96
281,18
281,54
288,95
332,68
345,96
414,96
285,35
288,03




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=57038&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=57038&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57038&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 axis13.7839881728016
y axis25.6005839229664
Correlation
correlation used in KDE0.475920400264707
correlation(x,y)0.475920400264707

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 13.7839881728016 \tabularnewline
y axis & 25.6005839229664 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.475920400264707 \tabularnewline
correlation(x,y) & 0.475920400264707 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57038&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]13.7839881728016[/C][/ROW]
[ROW][C]y axis[/C][C]25.6005839229664[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.475920400264707[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.475920400264707[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57038&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57038&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 axis13.7839881728016
y axis25.6005839229664
Correlation
correlation used in KDE0.475920400264707
correlation(x,y)0.475920400264707



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')