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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 10:54:58 -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/t1226426167ovuopm4b9r3qgrn.htm/, Retrieved Sat, 18 May 2024 17:59:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23784, Retrieved Sat, 18 May 2024 17:59:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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] [Workshop 4] [2007-10-30 14:37:46] [c8ea599e5a03d5b991b7fa762eaf839d]
F R  D    [Bivariate Kernel Density Estimation] [Q1 Bivariate Density] [2008-11-11 17:54:58] [35348cd8592af0baf5f138bd59921307] [Current]
Feedback Forum
2008-11-22 20:05:07 [Nilay Erdogdu] [reply] 
De densiteit wordt groter op een zelde oppervlakte. Dit wordt aangetoond door de hoogtelijnen (kleur). De samenvattende lijn vertoont eenzelfde verband als de hoogtelijnen. De punten die buiten de hoogtelijnen vallen, worden meeberekend om de helling van de rechte te tekenen. De vraag is of er een verband bestaat. Er is een positieve lijn aanwezig, heeft dat een betekenis? We zien dat de twee kernels die op de hoogtelijn liggen, een verband hebben.
2008-11-23 16:35:54 [Stéphanie Claes] [reply] 
Er wordt gebruik gemaakt van een hoogtelijn die punten met gelijke dichtheid met elkaar verbindt. => betrouwbaarheidsinterval in kaart brengen door te kijken welke punten bij elkaar liggen.
De Bivariate Density geeft meer informatie dan een gewone scatterplot.

correlation used in KDE 0.706684285304976
correlation(x,y) 0.706684285304976

Aan de hand van de tabel kunnen we zien dat er toch wel een sterke correlatie aanwezig is, dit kunnen we ook aflezen op de grafiek.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,8
7,6
7,5
7,6
7,5
7,3
7,6
7,5
7,6
7,9
7,9
8,1
8,2
8,0
7,5
6,8
6,5
6,6
7,6
8,0
8,0
7,7
7,5
7,6
7,7
7,9
7,8
7,5
7,5
7,1
7,5
7,5
7,6
7,7
7,7
7,9
8,1
8,2
8,2
8,1
7,9
7,3
6,9
6,6
6,7
6,9
7,0
7,1
7,2
7,1
6,9
7,0
6,8
6,4
6,7
6,7
6,4
6,3
6,2
6,5
6,8
6,8
6,5
6,3
5,9
5,9
6,4
6,4
Dataseries Y:
Download CSV
Histogram 
9,0
9,1
8,7
8,2
7,9
7,9
9,1
9,4
9,5
9,1
9,0
9,3
9,9
9,8
9,4
8,3
8,0
8,5
10,4
11,1
10,9
9,9
9,2
9,2
9,5
9,6
9,5
9,1
8,9
9,0
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9,0
9,0
9,0
9,8
10,0
9,9
9,3
9,0
9,0
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,8
7,9
7,9
8,0
7,9
7,5
7,2
6,9
6,6
6,7
7,3
7,5

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=23784&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=23784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23784&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 axis0.220124743810687
y axis0.255321342612492
Correlation
correlation used in KDE0.706684285304976
correlation(x,y)0.706684285304976

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.220124743810687 \tabularnewline
y axis & 0.255321342612492 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.706684285304976 \tabularnewline
correlation(x,y) & 0.706684285304976 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23784&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.220124743810687[/C][/ROW]
[ROW][C]y axis[/C][C]0.255321342612492[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.706684285304976[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.706684285304976[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23784&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 axis0.220124743810687
y axis0.255321342612492
Correlation
correlation used in KDE0.706684285304976
correlation(x,y)0.706684285304976


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')