Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_bidensity.wasp

Title produced by software

Bivariate Kernel Density Estimation

Date of computation

Sun, 09 Nov 2008 14:10:08 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/09/t122626509629mnsqf51iuoy9i.htm/, Retrieved Sun, 19 May 2024 10:23:55 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22877, Retrieved Sun, 19 May 2024 10:23:55 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

185

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Testing Population Proportion - Critical Value] [vraag 1] [2008-11-09 20:15:31] [c45c87b96bbf32ffc2144fc37d767b2e]
- RM    [Minimum Sample Size - Testing Proportions] [vraag 4] [2008-11-09 20:51:51] [c45c87b96bbf32ffc2144fc37d767b2e]
F RM D      [Bivariate Kernel Density Estimation] [vraag 1] [2008-11-09 21:10:08] [3dc594a6c62226e1e98766c4d385bfaa] [Current]

Feedback Forum

2008-11-24 20:23:10 [Michaël De Kuyer] [reply] 
Via de bivariate Kernel density kan je op een makkelijke manier twee variabelen met elkaar vergelijken. Bij deze techniek wordt gebruik gemaakt van hoogtelijnen die punten van gelijke dichtheid met elkaar verbinden. Op de grafiek kan je zien dat er verschillende zones voorkomen door de kleurverandering. De rode zone duidt op een sterke correlatie, de groene en de gele duiden op een eerdere zwakke correlatie. 
Door deze methode is men in staat beter clusters te zien. 
 
In dit voorbeeld is er duidelijk een sterke correlatie tussen de twee tijdreeksen. 
 

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Dataseries Y:

Download CSV

Histogram

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22877&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22877&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22877&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Bandwidth
x axis	182.918277142249
y axis	328.400939728379
Correlation
correlation used in KDE	0.927227927370034
correlation(x,y)	0.927227927370034

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 182.918277142249 \tabularnewline
y axis & 328.400939728379 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.927227927370034 \tabularnewline
correlation(x,y) & 0.927227927370034 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22877&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]182.918277142249[/C][/ROW]
[ROW][C]y axis[/C][C]328.400939728379[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.927227927370034[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.927227927370034[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22877&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22877&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Bandwidth
x axis	182.918277142249
y axis	328.400939728379
Correlation
correlation used in KDE	0.927227927370034
correlation(x,y)	0.927227927370034

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 98 ; par2 = 0.8571 ; par3 = 0.69 ; par4 = 0.05 ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code