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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 05:17:20 -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/t1226319594qnsmhce595l64fo.htm/, Retrieved Mon, 20 May 2024 02:42:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22987, Retrieved Mon, 20 May 2024 02:42:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153

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] [Bivariate Kernel ...] [2008-11-10 12:17:20] [e515c0250d6233b5d2604259ab52cebe] [Current]
F RMPD    [Hierarchical Clustering] [Q2 Various EDA] [2008-11-10 14:22:59] [5161246d1ccc1b670cc664d03050f084]
F RMPD    [Box-Cox Linearity Plot] [Q3 Various EDA] [2008-11-10 14:27:51] [5161246d1ccc1b670cc664d03050f084]
Feedback Forum
2008-11-21 11:50:18 [Hidde Van Kerckhoven] [reply] 
Er is inderdaad sprake van een positieve correlatie. Ook kunnen we zien dat er maar 1 cluster is. De punten in het rood betekenen dat er een hoge density is.
2008-11-23 16:16:21 [3cf9a3845ba92f3decccf252cabc2ee1] [reply] 
De student bekijkt hier de Bivariate Kernel Density. Bij deze methode worden punten met eenzelfde dichtheid verbonden en creeeren zo een soort van hoogtelijnen. We zien ook een positieve correlatie. Deze wordt weergegeven door de stijgende recht waarrond de punten zich bevinden. We kunnen ook aflezen dat de correlatie 0,92 bedraagt.
2008-11-23 16:38:53 [Davy De Nef] [reply] 
Mijn naam werd in de vorige post blijkbaar niet meegegeven. Vandaar dat ik deze comment even opnieuw post.
De student bekijkt hier de Bivariate Kernel Density. Bij deze methode worden punten met eenzelfde dichtheid verbonden en creeeren zo een soort van hoogtelijnen. We zien ook een positieve correlatie. Deze wordt weergegeven door de stijgende recht waarrond de punten zich bevinden. We kunnen ook aflezen dat de correlatie 0,92 bedraagt.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
136,5
146,4
157,7
148,7
154,6
152,1
144,8
142,1
157
159,1
164
151,5
135,9
138,5
161
151,7
142,9
157,4
138,9
141
150,9
149,9
153
144,3
128,1
123,3
155,9
144,1
134,1
153,1
131
129,8
139,9
135,6
126,8
134,4
113,5
107,5
133,8
119
125,9
130,1
114,2
111,6
131,2
124,1
127,1
123,4
100,7
100,3
121,6
110,5
110,3
122,7
102,6
101,8
113,6
107,2
116,8
112,5
Dataseries Y:
Download CSV
Histogram 
154,2
175,8
187,6
169,9
182,3
179,4
171,5
166,6
171,8
164,3
172,6
163
142,2
149,7
168,4
156,5
150,4
170,6
150,1
151,5
159,5
155,2
154,8
156,5
134,2
135,9
156,4
144,2
143,7
164,8
140,2
132,2
162
145
146,3
145,5
124,4
126
146,8
130,8
133,6
145,7
122,8
118,5
149,5
129,9
134,8
133,3
117,2
120,2
136,4
118,5
126,7
137,5
116,3
113,3
136,6
112,9
128,6
126,8

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'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=22987&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=22987&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22987&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 axis8.63459560472893
y axis10.5383775212030
Correlation
correlation used in KDE0.92692448668605
correlation(x,y)0.92692448668605

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 8.63459560472893 \tabularnewline
y axis & 10.5383775212030 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.92692448668605 \tabularnewline
correlation(x,y) & 0.92692448668605 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22987&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]8.63459560472893[/C][/ROW]
[ROW][C]y axis[/C][C]10.5383775212030[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.92692448668605[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.92692448668605[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22987&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22987&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 axis8.63459560472893
y axis10.5383775212030
Correlation
correlation used in KDE0.92692448668605
correlation(x,y)0.92692448668605


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')