FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 06 Nov 2008 09:10:23 -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/t1225987861qwtmlgqswffdi4n.htm/, Retrieved Tue, 14 May 2024 02:10:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22295, Retrieved Tue, 14 May 2024 02:10:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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] [Q1 prijsindex exc...] [2007-11-05 09:56:01] [ede03b06b9ae6a59763c2cc70a5f12fe]
F    D    [Bivariate Kernel Density Estimation] [Q1 prijsindex exc...] [2008-11-06 16:10:23] [1b288879226ab9a3cab0c803857233cc] [Current]
Feedback Forum
2008-11-24 21:44:06 [Niels Herremans] [reply] 
Er is hier inderdaad sprake van een hoge positieve correlatie. De hoogtelijnen verbinden de punten met een zelfde dichtheid en ee nrode kleur wijst op een hoge dichtheid. Op de grafiek is te zien dat de punten en clusters dicht bij de rechte liggen.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
96.9
98.0
97.9
100.9
103.9
103.1
102.5
104.3
102.6
101.7
102.8
105.4
110.9
113.5
116.3
124.0
128.8
133.5
132.6
128.4
127.3
126.7
123.3
123.2
124.4
128.2
128.7
135.7
139.0
145.4
142.4
137.7
137.0
137.1
139.3
139.6
140.4
142.3
148.3
157.7
161.6
161.7
171.8
185.1
176.7
184.4
183.0
180.9
187.0
189.9
193.8
194.5
198.7
204.7
213.2
214.7
211.0
213.2
206.3
210.8

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=22295&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=22295&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22295&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 axis17.3605888925838
y axis12.2851537636829
Correlation
correlation used in KDE0.939310769248664
correlation(x,y)0.939310769248664

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 17.3605888925838 \tabularnewline
y axis & 12.2851537636829 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.939310769248664 \tabularnewline
correlation(x,y) & 0.939310769248664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22295&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]17.3605888925838[/C][/ROW]
[ROW][C]y axis[/C][C]12.2851537636829[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.939310769248664[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.939310769248664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22295&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22295&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 axis17.3605888925838
y axis12.2851537636829
Correlation
correlation used in KDE0.939310769248664
correlation(x,y)0.939310769248664


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')