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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 computationFri, 07 Nov 2008 07:34:40 -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/07/t1226068575dqrq3654kn4rdly.htm/, Retrieved Sun, 19 May 2024 07:00:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22513, Retrieved Sun, 19 May 2024 07:00:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact147

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 density...] [2008-11-07 14:34:40] [a8228479d4547a92e2d3f176a5299609] [Current]
Feedback Forum
2008-11-23 13:01:56 [Stéphanie Claes] [reply] 
We gebruiken een hoogtelijn die punten met gelijke dichtheid met elkaar verbindt (het betrouwbaarheidsinterval in kaart brengen door te kijken welke punten bij elkaar liggen). De bivariate density geeft meer informatie dan de gewone scatterplot.
Als we kijken naar de tabel dan kunnen we daar de correlatie aflezen :

correlation used in KDE 0.311426992229758
correlation(x,y) 0.311426992229758

We kunnen dus besluiten dat de correlatie niet zo hoog is, maar er is wel correlatie. Dat kunnen we ook zien op de grafiek, de munten volgen ongeveer een lijn, er vallen geen clusters buiten.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
113,5
121,2
130,4
115,2
117,9
110,7
107,6
124,3
115,1
112,5
127,9
117,4
119,3
130,4
126
125,4
130,5
115,9
108,7
124
119,4
118,6
131,3
111,1
124,8
132,3
126,7
131,7
130,9
122,1
113,2
133,6
119,2
129,4
131,4
117,1
130,5
132,3
140,8
137,5
128,6
126,7
120,8
139,3
128,6
131,3
136,3
128,8
133,2
136,3
151,1
145
134,4
135,7
128,7
129,2
138,6
132,7
132,5
135,2
Dataseries Y:
Download CSV
Histogram 
41,1
58
63
53,8
54,7
55,5
56,1
69,6
69,4
57,2
68
53,3
47,9
60,8
61,7
57,8
51,4
50,5
48,1
58,7
54
56,1
60,4
51,2
50,7
56,4
53,3
52,6
47,7
49,5
48,5
55,3
49,8
57,4
64,6
53
41,5
55,9
58,4
53,5
50,6
58,5
49,1
61,1
52,3
58,4
65,5
61,7
45,1
52,1
59,3
57,9
45
64,9
63,8
69,4
71,1
62,9
73,5
62,6

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=22513&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=22513&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22513&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 axis3.36603641013937
y axis3.62457809981926
Correlation
correlation used in KDE0.311426992229758
correlation(x,y)0.311426992229758

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.36603641013937 \tabularnewline
y axis & 3.62457809981926 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.311426992229758 \tabularnewline
correlation(x,y) & 0.311426992229758 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22513&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.36603641013937[/C][/ROW]
[ROW][C]y axis[/C][C]3.62457809981926[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.311426992229758[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.311426992229758[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22513&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22513&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 axis3.36603641013937
y axis3.62457809981926
Correlation
correlation used in KDE0.311426992229758
correlation(x,y)0.311426992229758


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')