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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 computationMon, 10 Nov 2008 08:56:50 -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/Nov/10/t12263327452n7o0kzoawp9gch.htm/, Retrieved Sun, 19 May 2024 09:23:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23115, Retrieved Sun, 19 May 2024 09:23:42 +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)
F     [Partial Correlation] [Opdracht 6Q1 Part...] [2008-11-10 13:54:43] [aa5573c1db401b164e448aef050955a1]
- RMPD  [Bivariate Kernel Density Estimation] [Bivariate KDE bou...] [2008-11-10 14:57:46] [aa5573c1db401b164e448aef050955a1]
-    D    [Bivariate Kernel Density Estimation] [Bivariate KDE Bou...] [2008-11-10 15:04:02] [aa5573c1db401b164e448aef050955a1]
-    D        [Bivariate Kernel Density Estimation] [Opdracht 6 Bouwpr...] [2008-11-10 15:56:50] [8a1195ff8db4df756ce44b463a631c76] [Current]
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Dataseries X:
97.4
97
105.4
102.7
98.1
104.5
97.2
89.9
109.8
111.7
98.6
96.9
95.1
97
112.7
102.9
97.4
111.4
104.1
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
104.8
95.7
113.2
105.9
108.8
102.3
99
100.7
115.5
100.7
109.9
114.6
107.55
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
110.7
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1
Dataseries Y:
74.8
93.1
103.9
83.9
77.7
141.5
58.9
75.3
108.4
91
84.6
179.8
85.6
76.4
109.7
99.1
86.7
111.4
78.4
76.7
114.2
99.7
94.2
173.5
83.1
88.9
132
122.1
105.1
133.7
63.6
112.7
120.5
112
126.2
209.2
91
116.7
137.6
108.1
136.6
152.3
114.3
120.7
131.8
129.4
187.5
189.5
109.2
158.1
176.2
125.5
155
170.3
99.4
139.2
169.6
136.1
168.2
318.6
154.1
161.4
183.4
167.2
205.3




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=23115&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=23115&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23115&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 axis3.14517390490437
y axis17.4425200408636
Correlation
correlation used in KDE0.365112388388766
correlation(x,y)0.365112388388766

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.14517390490437 \tabularnewline
y axis & 17.4425200408636 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.365112388388766 \tabularnewline
correlation(x,y) & 0.365112388388766 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23115&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.14517390490437[/C][/ROW]
[ROW][C]y axis[/C][C]17.4425200408636[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.365112388388766[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.365112388388766[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23115&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23115&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 axis3.14517390490437
y axis17.4425200408636
Correlation
correlation used in KDE0.365112388388766
correlation(x,y)0.365112388388766



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')