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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 computationThu, 13 Nov 2008 07:53:38 -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/t1226588077g3kaqe48ffq9s3d.htm/, Retrieved Sun, 19 May 2024 10:04:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24637, Retrieved Sun, 19 May 2024 10:04:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact184

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Testing Sample Mean with known Variance - Confidence Interval] [Pork quality test...] [2008-11-12 13:22:58] [7a664918911e34206ce9d0436dd7c1c8]
F RMPD    [Bivariate Kernel Density Estimation] [Various EDA topics] [2008-11-13 14:53:38] [c4248bbb85fa4e400deddbf50234dcae] [Current]
Feedback Forum
2008-11-16 14:12:12 [Ken Wright] [reply] 
Hier zijn de waarde iets meer verspreid als bij de vorige. Je kan zien dat de rode vlakte meer gespreid is, maar toch liggen ze mooi rond de regressierechte. De hoogtelijnen zijn ook ellips van vorm en wijzen naar rechtsboven dus er is ook een correlatief positief verband.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.1
100.6
103.1
95.5
90.5
90.9
88.8
90.7
94.3
104.6
111.1
110.8
107.2
99
99
91
96.2
96.9
96.2
100.1
99
115.4
106.9
107.1
99.3
99.2
108.3
105.6
99.5
107.4
93.1
88.1
110.7
113.1
99.6
93.6
98.6
99.6
114.3
107.8
101.2
112.5
100.5
93.9
116.2
112
106.4
95.7
96
95.8
103
102.2
98.4
111.4
86.6
91.3
107.9
101.8
104.4
93.4
100.1
98.5
112.9
101.4
107.1
110.8
90.3
95.5
111.4
113
107.5
95.9
106.3
105.2
117.2
106.9
108.2
113
97.2
99.9
108.1
118.1
109.1
93.3
112.1
Dataseries Y:
Download CSV
Histogram 
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7

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=24637&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=24637&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24637&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 axis3.38688594334299
y axis4.60713319379022
Correlation
correlation used in KDE0.61998535500533
correlation(x,y)0.61998535500533

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.38688594334299 \tabularnewline
y axis & 4.60713319379022 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.61998535500533 \tabularnewline
correlation(x,y) & 0.61998535500533 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=24637&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.38688594334299[/C][/ROW]
[ROW][C]y axis[/C][C]4.60713319379022[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.61998535500533[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.61998535500533[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=24637&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24637&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 axis3.38688594334299
y axis4.60713319379022
Correlation
correlation used in KDE0.61998535500533
correlation(x,y)0.61998535500533


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')