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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 10:09:55 -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/t122659626126hfiv805dov4e4.htm/, Retrieved Tue, 28 May 2024 05:19:01 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24711, Retrieved Tue, 28 May 2024 05:19:01 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

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] [EDA various q1] [2008-11-13 17:09:55] [3452c99afdd85d4fde81272403cd85da] [Current]
-    D    [Bivariate Kernel Density Estimation] [verbetering] [2008-11-20 14:00:07] [3a9fc6d5b5e0e816787b7dbace57e7cd]
Feedback Forum
2008-11-20 14:03:37 [Gert-Jan Geudens] [reply] 
De student heeft deze module verkeerd geïnterpreteerd. Hij heeft de datum op de y-as gezet wat uiteraard niet correct. Het is de bedoeling om de correlatie te berekenen tussen 2 tijdreeksen. We zullen even de tijdreeks van de student gebruiken om dit te illustreren aan de hand van een voorbeeld.

www.freestatistics.org/blog/date/2008/Nov/20/t122718967909l24khg8mn3r13.htm

Uit deze plot kunnen we duidelijk afleiden dat er een groot positief verband is tussen de niet-werkende werkzoekenden -25jaar en het totaal van de niet-werkende werkzoekenden.

Dit zien we aan de hand van de positief gerichte ovale vormen van de hoogtelijnen.

Deze berekening moet de student nog toepassen voor de andere variabelen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867
120327
117008
108811
Dataseries Y:
Download CSV
Histogram 
31/10/2007
30/11/2007
31/12/2007
31/01/2008
29/02/2008
31/03/2008
30/04/2008
31/05/2008
30/06/2008
31/07/2008
31/08/2008
30/09/2008
31/10/2008

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24711&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]1 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=24711&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24711&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Bandwidth
x axis8508.30682543107
y axis0.000738428438015644
Correlation
correlation used in KDE-0.175048672642320
correlation(x,y)-0.175048672642320

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 8508.30682543107 \tabularnewline
y axis & 0.000738428438015644 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.175048672642320 \tabularnewline
correlation(x,y) & -0.175048672642320 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24711&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]8508.30682543107[/C][/ROW]
[ROW][C]y axis[/C][C]0.000738428438015644[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.175048672642320[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.175048672642320[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24711&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24711&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 axis8508.30682543107
y axis0.000738428438015644
Correlation
correlation used in KDE-0.175048672642320
correlation(x,y)-0.175048672642320


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')