Free Statistics

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Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareBivariate Kernel Density Estimation
Date of computationWed, 19 Dec 2012 08:29:57 -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/2012/Dec/19/t1355923819lbuhcsk0nrn52x8.htm/, Retrieved Fri, 01 Nov 2024 00:29:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=201920, Retrieved Fri, 01 Nov 2024 00:29:50 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Connected vs Sepa...] [2010-10-04 07:40:49] [b98453cac15ba1066b407e146608df68]
- RM      [Bivariate Kernel Density Estimation] [Paper2012: Bivari...] [2012-12-19 13:29:57] [86f0addf4b5362ca5a545029cdfac14b] [Current]
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Dataseries X:
34
33
29
34
32
35
41
27
40
40
36
40
43
40
33
37
32
26
36
39
38
34
35
41
42
36
39
33
33
36
37
36
34
32
35
39
30
25
29
39
31
26
28
40
32
35
32
41
34
36
38
34
32
34
32
40
43
35
45
36
39
31
36
36
37
40
35
36
32
36
37
42
37
36
36
33
37
35
37
28
33
45
38
43
37
36
40
39
43
32
37
34
44
35
34
37
40
36
44
35
34
40
34
39
36
40
37
35
45
39
39
37
38
46
37
27
33
42
33
33
33
38
37
35
33
39
38
39
38
30
43
34
39
36
32
37
42
40
35
39
34
28
30
36
31
34
33
37
40
39
42
47
38
38
40
37
29
37
37
33
31
36
37
39
35
33
37
42
31
32
36
32
40
32
30
37
42
37
47
37
31
41
44
40
37
33
35
40
38
36
36
35
30
37
43
33
39
38
40
29
35
37
26
28
38
29
35
38
39
44
33
35
42
30
36
40
39
36
37
37
37
36
30
32
35
42
41
35
33
39
34
39
41
34
30
29
33
40
32
37
37
36
41
34
38
40
42
32
40
38
35
34
38
24
39
42
44
35
37
34
41
33
42
30
30
40
49
39
29
39
35
35
34
24
47
24
30
34
41
32
32
35
37
40
45
35
39
46
33
40
35
38
36
34
30
44
37
36
37
34
43
31
34
38
38
34
26
36
35
37
40
43
29
30
36
38
43
41
31
36
44
35
42
31
38
34
40
41
30
43
Dataseries Y:
30
28
31
35
35
37
39
31
38
37
37
35
37
42
28
37
36
37
33
40
30
36
33
40
37
37
39
35
36
34
36
32
33
27
37
32
31
31
32
37
25
30
37
37
40
35
35
43
32
42
35
27
30
31
36
36
41
34
36
33
35
28
33
38
37
39
34
32
36
36
35
33
42
36
33
36
32
35
38
33
32
38
39
39
39
30
38
38
42
41
31
39
40
31
34
23
28
36
41
29
31
33
35
35
34
40
34
36
35
39
33
37
40
32
37
27
35
37
32
31
31
38
34
30
34
37
38
33
35
27
34
35
39
35
34
36
36
32
39
40
35
31
35
38
37
31
32
35
39
31
39
48
33
36
40
37
34
42
39
28
26
30
30
39
37
40
38
35
33
34
33
41
36
27
33
38
31
31
46
33
34
47
36
38
32
33
34
34
37
37
41
27
31
38
30
36
30
34
32
29
29
39
32
30
39
30
40
41
38
37
33
34
36
39
41
42
38
40
32
40
37
36
28
36
35
32
38
32
39
39
31
33
46
38
24
28
35
39
37
38
38
32
36
28
38
28
37
28
40
34
33
32
30
33
37
39
42
36
35
32
35
33
36
31
32
38
46
39
31
39
36
37
33
22
42
28
28
31
36
37
35
31
37
38
46
40
43
49
39
37
36
31
32
38
37
36
21
32
36
35
39
28
42
36
41
30
18
37
28
39
40
44
26
34
37
37
32
29
31
32
44
39
39
35
36
33
35
35
30
38




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 2 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201920&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201920&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201920&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'Gertrude Mary Cox' @ cox.wessa.net







Bandwidth
x axis1.49671962080113
y axis1.30492764651663
Correlation
correlation used in KDE0.52595026181494
correlation(x,y)0.52595026181494

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.49671962080113 \tabularnewline
y axis & 1.30492764651663 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.52595026181494 \tabularnewline
correlation(x,y) & 0.52595026181494 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=201920&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.49671962080113[/C][/ROW]
[ROW][C]y axis[/C][C]1.30492764651663[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.52595026181494[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.52595026181494[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=201920&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=201920&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 axis1.49671962080113
y axis1.30492764651663
Correlation
correlation used in KDE0.52595026181494
correlation(x,y)0.52595026181494



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 ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')