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Description of Statistical Computation

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 computationTue, 11 Nov 2008 07:24:07 -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/11/t1226415735gqdu521116yab5r.htm/, Retrieved Mon, 20 May 2024 02:41:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23561, Retrieved Mon, 20 May 2024 02:41:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Bivariate Kernel Density Estimation] [bivariate density...] [2008-11-11 14:24:07] [09074fbe368d26382bb94e5bb318a104] [Current]
Feedback Forum
2008-11-18 10:54:51 [Loïque Verhasselt] [reply] 
Juiste berekeningswijze hier gebruikt. De student geeft hier alle 3 de densityplots, om elke variabele uit te zetten tegen een andere. Zo krijgen we het beste een verband te zien dat ook de correlaties volgt. Dit vinden we in de partial correlation. Bij deze student verloopt die positief tussen de 0,30 en 0,60 wat een redelijk goede positieve samenhang aangeeft. Het was misschien handiger om wanneer men het trivariate scatterplot berekende men met 1klik alle bivariate densityplots krijgt.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,1
100,6
103,1
95,5
90,5
90,9
88,8
90,7
94,3
104,6
111,1
110,8
107,2
99
99
91
96,2
96,9
96,2
100,1
99
115,4
106,9
107,1
99,3
99,2
108,3
105,6
99,5
107,4
93,1
88,1
110,7
113,1
99,6
93,6
98,6
99,6
114,3
107,8
101,2
112,5
100,5
93,9
116,2
112
106,4
95,7
96
95,8
103
102,2
98,4
111,4
86,6
91,3
107,9
101,8
104,4
93,4
100,1
98,5
112,9
101,4
107,1
110,8
90,3
95,5
111,4
113
107,5
95,9
106,3
105,2
117,2
106,9
108,2
113
97,2
99,9
108,1
118,1
109,1
93,3
112,1
Dataseries Y:
Download CSV
Histogram 
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23561&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23561&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23561&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Bandwidth
x axis3.38688594334299
y axis4.60713319379022
Correlation
correlation used in KDE0.61998535500533
correlation(x,y)0.61998535500533

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.38688594334299 \tabularnewline
y axis & 4.60713319379022 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.61998535500533 \tabularnewline
correlation(x,y) & 0.61998535500533 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23561&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.38688594334299[/C][/ROW]
[ROW][C]y axis[/C][C]4.60713319379022[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.61998535500533[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.61998535500533[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23561&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23561&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Bandwidth
x axis3.38688594334299
y axis4.60713319379022
Correlation
correlation used in KDE0.61998535500533
correlation(x,y)0.61998535500533


Figures (Output of Computation)

Input Parameters & R Code

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')