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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 computationSat, 08 Nov 2008 09:00:44 -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/08/t1226160093wv6tq7yq1clumuj.htm/, Retrieved Sun, 19 May 2024 08:50:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22613, Retrieved Sun, 19 May 2024 08:50:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

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] [Various EDA topic...] [2008-11-08 16:00:44] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
Feedback Forum
2008-11-24 18:04:34 [Niels Herremans] [reply] 
De student heeft hier de Bivariate Kernel Density juist berekend maar heeft geen conclusies getrokken. Er is hier srake van een positieve correlatie van 0.69. In de grafiek worden punten met een gelijke density met elkaar verbonden en zo ontstaan er 'hoogtelijnen'. Waar een rode kleur is, is er een hoge density. We kunnen hier ook zien dat er meer dan 1 cluster is. We zien ook een stijgende rechte waarrond de punten en clusters liggen. De stijgende rechte duidt op de positieve correlatie.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106,60
106,80
107,00
107,10
107,30
107,40
107,60
107,70
107,90
108,20
108,30
108,50
108,92
109,23
109,41
109,65
109,91
110,01
110,20
110,49
110,57
110,72
110,94
111,09
111,28
111,41
111,62
111,76
111,89
112,04
112,12
112,30
112,47
112,59
112,78
112,73
112,99
113,10
113,33
113,38
113,68
113,65
113,81
113,88
114,02
114,25
114,28
114,38
114,73
114,97
115,05
115,29
115,37
115,54
115,76
115,92
116,02
116,21
116,26
116,51
Dataseries Y:
Download CSV
Histogram 
0,33
0,33
0,32
0,33
0,34
0,36
0,34
0,33
0,35
0,31
0,28
0,26
0,26
0,26
0,29
0,30
0,30
0,28
0,29
0,29
0,32
0,33
0,29
0,31
0,33
0,36
0,39
0,30
0,27
0,28
0,29
0,30
0,30
0,30
0,31
0,30
0,31
0,29
0,32
0,33
0,35
0,35
0,36
0,40
0,40
0,47
0,43
0,38
0,38
0,40
0,45
0,47
0,45
0,50
0,54
0,55
0,59
0,51
0,50
0,50

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 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=22613&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]3 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=22613&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22613&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Bandwidth
x axis1.34199569990420
y axis0.0223288570000657
Correlation
correlation used in KDE0.685083610140651
correlation(x,y)0.685083610140651

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.34199569990420 \tabularnewline
y axis & 0.0223288570000657 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.685083610140651 \tabularnewline
correlation(x,y) & 0.685083610140651 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22613&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.34199569990420[/C][/ROW]
[ROW][C]y axis[/C][C]0.0223288570000657[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.685083610140651[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.685083610140651[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22613&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22613&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 axis1.34199569990420
y axis0.0223288570000657
Correlation
correlation used in KDE0.685083610140651
correlation(x,y)0.685083610140651


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')