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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 computationMon, 10 Nov 2008 03:14:54 -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/10/t12263121718a20prk86lfld6e.htm/, Retrieved Sun, 19 May 2024 08:51:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22906, Retrieved Sun, 19 May 2024 08:51:32 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact207

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [Workshop 4 - EDA ...] [2007-11-01 08:12:46] [b3bb3ec527e23fa7d74d4348b38c8499]
F R  D    [Bivariate Kernel Density Estimation] [Bivariate Density] [2008-11-10 10:14:54] [6aa66640011d9b98524a5838bcf7301d] [Current]
Feedback Forum
2008-11-19 15:04:22 [Mehmet Yilmaz] [reply] 
De student heeft de berekening gemaakt maar geen uitleg gegeven.

Interpretatie van de Bivarlate kernel density:
Deze methode geeft clusters weer. In het midden van elke cluster ligt de intensiteit van de punten (observaties) heel dicht. Hoe verder je gaat van het midden, hoe minder de intensiteit.
Hoe dichter de clusters bij elkaar liggen, hoe groter de correlatie.
Je kan hierbij slechts 2 variabelen vergelijken.
2008-11-19 21:16:40 [Nathalie Koulouris] [reply] 
De student heeft inderdaad de juiste berekenig gemaakt maar niet verder gemotiveerd.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4,43
4,61
4,54
4,2
4,08
3,95
4,19
4,23
3,89
3,92
4,14
4,24
4,08
4,37
4,43
4,3
4,27
4,06
3,96
4,21
4,31
4,35
4,25
4,06
4
3,87
3,71
3,63
3,48
3,6
3,66
3,45
3,3
3,14
3,21
3,12
3,14
3,4
3,42
3,29
3,49
3,52
3,81
4,03
3,98
4,1
3,96
3,83
3,72
3,82
3,76
3,98
4,14
4
4,13
4,28
4,46
4,63
4,49
4,41
4,5
4,39
4,33
4,45
4,17
4,13
4,33
4,47
4,63
4,9
Dataseries Y:
Download CSV
Histogram 
88,3
88,6
91
91,5
95,4
98,7
99,9
98,6
100,3
100,2
100,4
101,4
103
109,1
111,4
114,1
121,8
127,6
129,9
128
123,5
124
127,4
127,6
128,4
131,4
135,1
134
144,5
147,3
150,9
148,7
141,4
138,9
139,8
145,6
147,9
148,5
151,1
157,5
167,5
172,3
173,5
187,5
205,5
195,1
204,5
204,5
201,7
207
206,6
210,6
211,1
215
223,9
238,2
238,9
229,6
232,2
222,1
221,6
227,3
221
213,6
243,4
253,8
265,3
268,2
268,5
266,9

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22906&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22906&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22906&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'Gwilym Jenkins' @ 72.249.127.135






Bandwidth
x axis0.170372270223427
y axis16.5740571416571
Correlation
correlation used in KDE0.229422209358499
correlation(x,y)0.229422209358499

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.170372270223427 \tabularnewline
y axis & 16.5740571416571 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.229422209358499 \tabularnewline
correlation(x,y) & 0.229422209358499 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22906&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.170372270223427[/C][/ROW]
[ROW][C]y axis[/C][C]16.5740571416571[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.229422209358499[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.229422209358499[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22906&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22906&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 axis0.170372270223427
y axis16.5740571416571
Correlation
correlation used in KDE0.229422209358499
correlation(x,y)0.229422209358499


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')