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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, 12 Dec 2008 05:35:54 -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/2008/Dec/12/t1229085386octp9ru52uc6240.htm/, Retrieved Fri, 17 May 2024 13:52:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32630, Retrieved Fri, 17 May 2024 13:52:57 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact186
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cross Correlation Function] [Cross Correlatie ...] [2008-12-12 09:25:56] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
- RMPD    [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-12-12 12:35:54] [b5110a3ab194da7214bdf478e0a05dbd] [Current]
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Dataseries X:
97.7
101.5
119.6
108.1
117.8
125.5
89.2
92.3
104.6
122.8
96.0
94.6
93.3
101.1
114.2
104.7
113.3
118.2
83.6
73.9
99.5
97.7
103.0
106.3
92.2
101.8
122.8
111.8
106.3
121.5
81.9
85.4
110.9
117.3
106.3
105.5
101.3
105.9
126.3
111.9
108.9
127.2
94.2
85.7
116.2
107.2
110.6
112.0
104.5
112.0
132.8
110.8
128.7
136.8
94.9
88.8
123.2
125.3
122.7
125.7
116.3
118.7
142.0
127.9
131.9
152.3
110.8
99.1
135.0
133.2
131.0
133.9
119.9
136.9
148.9
145.1
142.4
159.6
120.7
109.0
142.0
Dataseries Y:
98.5
97.0
103.3
99.6
100.1
102.9
95.9
94.5
107.4
116.0
102.8
99.8
109.6
103.0
111.6
106.3
97.9
108.8
103.9
101.2
122.9
123.9
111.7
120.9
99.6
103.3
119.4
106.5
101.9
124.6
106.5
107.8
127.4
120.1
118.5
127.7
107.7
104.5
118.8
110.3
109.6
119.1
96.5
106.7
126.3
116.2
118.8
115.2
110.0
111.4
129.6
108.1
117.8
122.9
100.6
111.8
127.0
128.6
124.8
118.5
114.7
112.6
128.7
111.0
115.8
126.0
111.1
113.2
120.1
130.6
124.0
119.4
116.7
116.5
119.6
126.5
111.3
123.5
114.2
103.7
129.5




Summary of computational 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 computational 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=32630&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]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=32630&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32630&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis8.6932342542798
y axis4.67149916614896
Correlation
correlation used in KDE0.635974061397394
correlation(x,y)0.635974061397394

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 8.6932342542798 \tabularnewline
y axis & 4.67149916614896 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.635974061397394 \tabularnewline
correlation(x,y) & 0.635974061397394 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32630&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]8.6932342542798[/C][/ROW]
[ROW][C]y axis[/C][C]4.67149916614896[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.635974061397394[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.635974061397394[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32630&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32630&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 axis8.6932342542798
y axis4.67149916614896
Correlation
correlation used in KDE0.635974061397394
correlation(x,y)0.635974061397394



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')