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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationThu, 13 Nov 2008 10:48:29 -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/13/t1226598564smxehkrx24ttqjp.htm/, Retrieved Sun, 19 May 2024 11:37:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24734, Retrieved Sun, 19 May 2024 11:37:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact116

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] [] [2008-11-13 17:48:29] [cae3b9b084628ae4df84563390017721] [Current]
Feedback Forum
2008-11-20 12:43:24 [Steven Vanhooreweghe] [reply] 
Het klopt hier wat je zegt. Je kan ook aan de cirkelvormige hoogtelijn zien dat er geen correlatie is.
2008-11-22 16:58:48 [Peter Van Doninck] [reply] 
Het klopt inderdaad dat de bivariate analyse cirkels als oplossing geeft. Hierdoor is er geen verband tussen de variabelen, wat de student correct antwoordt.
2008-11-22 17:31:31 [Peter Van Doninck] [reply] 
Er zijn ook te weinig gegevens gebruikt voor de analyse te doen!!!
2008-11-24 18:43:51 [Liese Drijkoningen] [reply] 
Ik kan volgende aanvullingen doen op het antwoord van de student.
De rechte lijn die door de grafiek loop, probeert de puntenwolk zo goed mogelijk te benaderen. De hoogtelijnen die we terug vinden proberen de derde dimensie voor te stellen. Deze dimensie stelt de dichtheid of de concentratie van de punten voor. Maar de dichtheid van de punten stelt eerder de waarschijnlijkheid voor dat de punten zich daar bevinden. Het heeft niet rechtstreeks met de derde dimensie te maken.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
248,4
268
267,9
263,2
263,2
333,8
312,3
295,4
283,3
287,6
265,7
Dataseries Y:
Download CSV
Histogram 
5,5
10,5
15,8
13,3
12
10,3
15
14,7
12,2
10,4
11,8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24734&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24734&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Bandwidth
x axis12.7335434972209
y axis1.5581327809381
Correlation
correlation used in KDE0.269831641923088
correlation(x,y)0.269831641923088

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 12.7335434972209 \tabularnewline
y axis & 1.5581327809381 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.269831641923088 \tabularnewline
correlation(x,y) & 0.269831641923088 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24734&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]12.7335434972209[/C][/ROW]
[ROW][C]y axis[/C][C]1.5581327809381[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.269831641923088[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.269831641923088[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24734&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 axis12.7335434972209
y axis1.5581327809381
Correlation
correlation used in KDE0.269831641923088
correlation(x,y)0.269831641923088


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')