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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 05:02:42 -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/t12264050409cr7fhnwy6hx0de.htm/, Retrieved Mon, 20 May 2024 06:32:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23352, Retrieved Mon, 20 May 2024 06:32:29 +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 kernel ...] [2008-11-11 12:02:42] [924502d03698cd41cacbcd1327858815] [Current]
Feedback Forum
2008-11-16 15:54:25 [Gert De la Haye] [reply] 
een vrij normale verdeling, de correlatierechte loopt door het 'hoogtepunt' van de verdeling, daar waar de meeste punten samenvallen (rood gekleurd)
2008-11-22 15:18:16 [Ilknur Günes] [reply] 
Bivariate Density geeft geen wetenschappelijke analyse, maar het doet je wel vragen stellen. Zo zie je dat het een vrij normale vedeling is, vermits de rechts door de 'kern' gaat
2008-11-23 14:31:45 [Chi-Kwong Man] [reply] 
Correct, deze grafiek gebruiken we omdat deze meer informatie geeft dan een scatterplot en een correlatieplot (beetje zoals een weerkaart). Dichtheid ~ waarschijnlijkheid.
2008-11-23 16:34:07 [Michaël De Kuyer] [reply] 
Het antwoord van de student is correct. Men kan inderdaad een rechte trekken door de kern van de grafiek. Toch zijn er enkele cirkels die afwijken van de rechte.

Post a new message

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
7,5
6,8
6,5
6,6
7,6
8
8
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
7,1
7,2
7,1
6,9
7
6,8
6,4
6,7
6,7
6,4
6,3
6,2
6,5
Dataseries Y:
Download CSV
Histogram 
9
9,1
8,7
8,2
7,9
7,9
9,1
9,4
9,5
9,1
9
9,3
9,9
9,8
9,4
8,3
8
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
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9
9
9
9,8
10
9,9
9,3
9
9
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,8
7,9
7,9
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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23352&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23352&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23352&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'Gwilym Jenkins' @ 72.249.127.135






Bandwidth
x axis0.208712779752709
y axis0.159010161741358
Correlation
correlation used in KDE0.547394401067946
correlation(x,y)0.547394401067946

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.208712779752709 \tabularnewline
y axis & 0.159010161741358 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.547394401067946 \tabularnewline
correlation(x,y) & 0.547394401067946 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23352&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.208712779752709[/C][/ROW]
[ROW][C]y axis[/C][C]0.159010161741358[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.547394401067946[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.547394401067946[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23352&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23352&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 axis0.208712779752709
y axis0.159010161741358
Correlation
correlation used in KDE0.547394401067946
correlation(x,y)0.547394401067946


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')