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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationThu, 13 Nov 2008 01:55:09 -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/t1226566705keae9m5jo25ve3x.htm/, Retrieved Sun, 19 May 2024 02:25:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24493, Retrieved Sun, 19 May 2024 02:25:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177

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] [Workshop 3 Q1 (bi...] [2008-11-13 08:55:09] [1a15026c70cce1c14dcfcc267c5d8133] [Current]
Feedback Forum
2008-11-18 09:06:09 [Angelique Van de Vijver] [reply] 
Hier is het verband weergegeven van algemen PIC grondstoffen en PIC levensmiddelen. Goede conclusie over de sterke correl
2008-11-18 09:10:51 [Angelique Van de Vijver] [reply] 
Het gaat hier dus over het verband tussen de algemene PIC grondstoffen en de PIC levensmiddelen. Goede conclusie over de sterke correlatie tussen deze 2 variabelen. Dit zie je aan het correlatiecijfer in de tabel (0.928).
Extra uitleg: Als je dus naar de clusters kijkt bij de bivariate kernel density, zie je dus weer ellipsen die naar rechtsboven gericht zijn. Wat dus wijst op een positieve correlatie. De clusters liggen ook rond de diagonaal wat dus ook wijst op een hoge correlatie.
2008-11-24 12:05:23 [Anouk Greeve] [reply] 
Er is inderdaad een sterke correlatie en dus een duidelijk verband tussen de algemene PIC grondstoffen en de PIC levensmiddelen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
118,4
121,4
128,8
131,7
141,7
142,9
139,4
134,7
125,0
113,6
111,5
108,5
112,3
116,6
115,5
120,1
132,9
128,1
129,3
132,5
131,0
124,9
120,8
122,0
122,1
127,4
135,2
137,3
135,0
136,0
138,4
134,7
138,4
133,9
133,6
141,2
151,8
155,4
156,6
161,6
160,7
156,0
159,5
168,7
169,9
169,9
185,9
190,8
195,8
211,9
227,1
251,3
256,7
251,9
251,2
270,3
267,2
243,0
229,9
187,2
Dataseries Y:
Download CSV
Histogram 
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145,0
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179,0
190,6
190,0
181,6
174,8
180,5
196,8
193,8
197,0
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244,0
234,7
250,2
265,7
287,6
283,3
295,4
312,3
333,8
347,7
383,2
407,1
413,6
362,7
321,9
239,4

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=24493&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=24493&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24493&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 axis9.5053394905359
y axis26.0689847803738
Correlation
correlation used in KDE0.928381013034265
correlation(x,y)0.928381013034265

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 9.5053394905359 \tabularnewline
y axis & 26.0689847803738 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.928381013034265 \tabularnewline
correlation(x,y) & 0.928381013034265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24493&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]9.5053394905359[/C][/ROW]
[ROW][C]y axis[/C][C]26.0689847803738[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.928381013034265[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.928381013034265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24493&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24493&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 axis9.5053394905359
y axis26.0689847803738
Correlation
correlation used in KDE0.928381013034265
correlation(x,y)0.928381013034265


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')