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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 computationThu, 18 Dec 2008 05:35:30 -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/18/t1229603767t47br9njttt0sle.htm/, Retrieved Sun, 12 May 2024 08:06:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34715, Retrieved Sun, 12 May 2024 08:06:22 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact151
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [Paper - Un. EDA -...] [2008-12-18 11:54:57] [85841a4a203c2f9589565c024425a91b]
- RMPD    [Bivariate Kernel Density Estimation] [Paper - Bivariate...] [2008-12-18 12:35:30] [07b7cf1321bc38017c2c7efcf91ca696] [Current]
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Dataseries X:
127,96
127,47
126,47
125,75
125,42
125,14
125,15
125,51
125,63
126,22
126,88
127,96
128,74
129,6
131,2
132,72
134,67
135,94
136,39
136,74
137,2
137,36
138,63
141,07
143,32
147,91
152,56
151,61
156,56
157,45
158,13
159,18
159,47
159,79
161,65
162,77
163,48
166,16
163,86
162,12
149,08
145,32
141,21
134,68
133,65
139,17
138,61
144,96
157,99
167,18
174,48
182,77
190,00
189,70
188,90
198,28
201,18
204,14
221,02
221,12
220,68
Dataseries Y:
20.72
21.45
22.09
21.53
23.35
23.57
26.42
25.21
26.44
29.34
29.40
33.05
28.38
26.01
29.31
30.36
35.75
36.15
34.21
37.91
38.70
42.12
42.16
39.80
37.36
38.35
42.60
41.25
42.16
46.94
47.43
47.06
50.18
50.13
43.23
40.04
40.37
42.21
37.00
39.74
42.68
46.29
46.97
48.73
52.37
50.05
54.04
57.78
64.72
63.41
64.36
66.03
72.14
76.60
86.97
93.48
95.59
81.89
70.55
50.38
36.25




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34715&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34715&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34715&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Bandwidth
x axis6.89245699767754
y axis5.27743551812422
Correlation
correlation used in KDE0.752861807645314
correlation(x,y)0.752861807645314

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 6.89245699767754 \tabularnewline
y axis & 5.27743551812422 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.752861807645314 \tabularnewline
correlation(x,y) & 0.752861807645314 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34715&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]6.89245699767754[/C][/ROW]
[ROW][C]y axis[/C][C]5.27743551812422[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.752861807645314[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.752861807645314[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34715&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34715&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 axis6.89245699767754
y axis5.27743551812422
Correlation
correlation used in KDE0.752861807645314
correlation(x,y)0.752861807645314



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')