Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_bidensity.wasp
Title produced by softwareBivariate Kernel Density Estimation
Date of computationThu, 06 Nov 2008 09:12:21 -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/06/t1225987971pzlp8ki8wlqxqik.htm/, Retrieved Tue, 14 May 2024 23:20:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22297, Retrieved Tue, 14 May 2024 23:20:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Kernel Density Estimation] [totaal grondstoff...] [2007-11-05 10:03:19] [ede03b06b9ae6a59763c2cc70a5f12fe]
F    D    [Bivariate Kernel Density Estimation] [totaal grondstoff...] [2008-11-06 16:12:21] [1b288879226ab9a3cab0c803857233cc] [Current]
Feedback Forum
2008-11-24 21:45:13 [Niels Herremans] [reply
Hier is er een heel groot verband tussen de 2 variabelen met de punten en hoogtelijnen die nagenoeg helemaal op de rechte liggen.

Post a new message
Dataseries X:
96.7
88.0
96.7
106.8
114.3
105.7
90.1
91.6
97.7
100.8
104.6
95.9
102.7
104.0
107.9
113.8
113.8
123.1
125.1
137.6
134.0
140.3
152.1
150.6
167.3
153.2
142.0
154.4
158.5
180.9
181.3
172.4
192.0
199.3
215.4
214.3
201.5
190.5
196.0
215.7
209.4
214.1
237.8
239.0
237.8
251.5
248.8
215.4
201.2
203.1
214.2
188.9
203.0
213.3
228.5
228.2
240.9
258.8
248.5
269.2
Dataseries Y:
96.8
91.2
97.1
104.9
110.9
104.8
94.1
95.8
99.3
101.1
104.0
99.0
105.4
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




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22297&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]2 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=22297&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22297&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Bandwidth
x axis18.1116066082722
y axis17.3605888925838
Correlation
correlation used in KDE0.993726597812152
correlation(x,y)0.993726597812152

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 18.1116066082722 \tabularnewline
y axis & 17.3605888925838 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.993726597812152 \tabularnewline
correlation(x,y) & 0.993726597812152 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22297&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]18.1116066082722[/C][/ROW]
[ROW][C]y axis[/C][C]17.3605888925838[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.993726597812152[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.993726597812152[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22297&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22297&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 axis18.1116066082722
y axis17.3605888925838
Correlation
correlation used in KDE0.993726597812152
correlation(x,y)0.993726597812152



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')