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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, 06 Nov 2009 06:48:01 -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/06/t1257515336lbh09911b0k7633.htm/, Retrieved Sat, 27 Apr 2024 16:42:47 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54309, Retrieved Sat, 27 Apr 2024 16:42:47 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbhschhwstws6p7.2
Estimated Impact168
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]
-   PD    [Bivariate Kernel Density Estimation] [Workshop 6] [2009-11-06 13:48:01] [682632737e024f9e62885141c5f654cd] [Current]
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Dataseries X:
150.85
147.79
141.96
148.39
147.71
150.6
151.18
152.24
157.19
154.62
157.22
159.7
160.55
149.66
151.69
154.13
151.48
153.34
155.8
158.87
156.09
156.3
156.4
154.09
161.32
160.12
155.17
154.51
151.38
152.59
153.98
154.91
153.01
155.09
155.53
161.86
166.03
164.54
164.33
163.21
159.95
164.18
167.13
166.8
166.29
168.07
167.1
163.53
168.28
169.07
165.84
163.88
157.33
161
163.54
161.21
158.92
160.18
159.9
164.46
Dataseries Y:
126.51
131.02
136.51
138.04
132.92
129.61
122.96
124.04
121.29
124.56
118.53
113.14
114.15
122.17
129.23
131.19
129.12
128.28
126.83
138.13
140.52
146.83
135.14
131.84
125.7
128.98
133.25
136.76
133.24
128.54
121.08
120.23
119.08
125.75
126.89
126.6
121.89
123.44
126.46
129.49
127.78
125.29
119.02
119.96
122.86
131.89
132.73
135.01
136.71
142.73
144.43
144.93
138.75
130.22
122.19
128.4
140.43
153.5
149.33
142.97




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54309&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54309&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54309&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Bandwidth
x axis2.84471494718907
y axis4.00727418747204
Correlation
correlation used in KDE0.0451963897353126
correlation(x,y)0.0451963897353126

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 2.84471494718907 \tabularnewline
y axis & 4.00727418747204 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.0451963897353126 \tabularnewline
correlation(x,y) & 0.0451963897353126 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54309&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]2.84471494718907[/C][/ROW]
[ROW][C]y axis[/C][C]4.00727418747204[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.0451963897353126[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.0451963897353126[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54309&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54309&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 axis2.84471494718907
y axis4.00727418747204
Correlation
correlation used in KDE0.0451963897353126
correlation(x,y)0.0451963897353126



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')