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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 computationThu, 13 Nov 2008 11:02:32 -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/t1226599493qu7dxkffmdl4ove.htm/, Retrieved Sun, 19 May 2024 11:12:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24743, Retrieved Sun, 19 May 2024 11:12:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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] [2008-11-13 18:02:32] [d300b7a0882cee7d84584ad37a3d4ede] [Current]
Feedback Forum
2008-11-20 10:47:23 [7bf28d4d60530086dbc44ae6b648927e] [reply] 
Bij een bivariate Kernel density plot gaan we het verband onderzoeken tussen 2 variablen. Wanneer je elipsvormige hoogtelijnen ziet, is er duidelijk een verband. De scatterplots zullen lineair zijn. Wanneer er cirkelvormige hoogtelijnen aanwezig zijn is er geen verband. Hier is duidelijk het laatste te zien. Er is dus geen verband tussen x en y.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
6,7
7,4
7,6
7,5
7,7
6,7
5,9
5,6
7,1
7,7
7,3
7,4
7,6
7,7
6,7
5,1
4,2
4
4,6
5,8
6,3
6,2
6,3
7,1
7,2
Dataseries Y:
Download CSV
Histogram 
8,5
9,3
9,5
9,5
8,9
8,6
7,5
8,5
10,3
11,6
11,9
12,5
12,7
12,7
11,5
10
9,8
10,4
11,7
13,7
15,6
16,3
16,4
17,1
16,8

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=24743&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=24743&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24743&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 axis0.471672001399314
y axis1.11497186707814
Correlation
correlation used in KDE0.109330482359631
correlation(x,y)0.109330482359631

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.471672001399314 \tabularnewline
y axis & 1.11497186707814 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.109330482359631 \tabularnewline
correlation(x,y) & 0.109330482359631 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24743&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.471672001399314[/C][/ROW]
[ROW][C]y axis[/C][C]1.11497186707814[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.109330482359631[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.109330482359631[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24743&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24743&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 axis0.471672001399314
y axis1.11497186707814
Correlation
correlation used in KDE0.109330482359631
correlation(x,y)0.109330482359631


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')