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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, 18 Dec 2008 10:08:12 -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/Dec/18/t1229620125770avrvkytsssiy.htm/, Retrieved Sun, 12 May 2024 10:26:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34892, Retrieved Sun, 12 May 2024 10:26:51 +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     [Univariate Data Series] [HPC Retail Sales] [2008-03-02 15:42:48] [74be16979710d4c4e7c6647856088456]
- RMPD    [Bivariate Kernel Density Estimation] [Paper 1] [2008-12-18 17:08:12] [0458bd763b171003ec052ce63099d477] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
90.70
94.30
104.60
111.10
110.80
107.20
99.00
99.00
91.00
96.20
96.90
96.20
100.10
99.00
115.40
106.90
107.10
99.30
99.20
108.30
105.60
99.50
107.40
93.10
88.10
110.70
113.10
99.60
93.60
98.60
99.60
114.30
107.80
101.20
112.50
100.50
93.90
116.20
112.00
106.40
95.70
96.00
95.80
103.00
102.20
98.40
111.40
86.60
91.30
107.90
101.80
104.40
93.40
100.10
98.50
112.90
101.40
107.10
110.80
90.30
95.50
111.40
113.00
107.50
95.90
106.30
105.20
117.20
106.90
108.20
113.00
97.20
99.90
108.10
118.10
109.10
93.30
112.10
111.80
112.50
116.30
110.30
117.10
103.40
96.20
Dataseries Y:
Download CSV
Histogram 
78.40
114.60
113.30
117.00
99.60
99.40
101.90
115.20
108.50
113.80
121.00
92.20
90.20
101.50
126.60
93.90
89.80
93.40
101.50
110.40
105.90
108.40
113.90
86.10
69.40
101.20
100.50
98.00
106.60
90.10
96.90
125.90
112.00
100.00
123.90
79.80
83.40
113.60
112.90
104.00
109.90
99.00
106.30
128.90
111.10
102.90
130.00
87.00
87.50
117.60
103.40
110.80
112.60
102.50
112.40
135.60
105.10
127.70
137.00
91.00
90.50
122.40
123.30
124.30
120.00
118.10
119.00
142.70
123.60
129.60
151.60
110.40
99.20
130.50
136.20
129.70
128.00
121.60
135.80
143.80
147.50
136.20
156.60
123.30
100.40

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=34892&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=34892&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34892&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 axis2.99006311411283
y axis8.57073381946338
Correlation
correlation used in KDE0.684629200251958
correlation(x,y)0.684629200251958

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 2.99006311411283 \tabularnewline
y axis & 8.57073381946338 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.684629200251958 \tabularnewline
correlation(x,y) & 0.684629200251958 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34892&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]2.99006311411283[/C][/ROW]
[ROW][C]y axis[/C][C]8.57073381946338[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.684629200251958[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.684629200251958[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34892&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34892&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 axis2.99006311411283
y axis8.57073381946338
Correlation
correlation used in KDE0.684629200251958
correlation(x,y)0.684629200251958


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')