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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, 12 Nov 2009 12:24:27 -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/2009/Nov/12/t1258053905xrje6erk0bz73ql.htm/, Retrieved Fri, 03 May 2024 18:56:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56373, Retrieved Fri, 03 May 2024 18:56:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bagplot] [3/11/2009] [2009-11-02 21:51:11] [b98453cac15ba1066b407e146608df68]
-    D  [Bagplot] [] [2009-11-12 19:16:45] [58e1a7a2c10f1de09acf218271f55dfd]
- RM        [Bivariate Kernel Density Estimation] [] [2009-11-12 19:24:27] [429631dabc57c2ce83a6344a979b9063] [Current]
-             [Bivariate Kernel Density Estimation] [] [2009-11-12 19:42:14] [58e1a7a2c10f1de09acf218271f55dfd]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
115.6
111.9
107
107.1
100.6
99.2
108.4
103
99.8
115
90.8
95.9
114.4
108.2
112.6
109.1
105
105
118.5
103.7
112.5
116.6
96.6
101.9
116.5
119.3
115.4
108.5
111.5
108.8
121.8
109.6
112.2
119.6
104.1
105.3
115
124.1
116.8
107.5
115.6
116.2
116.3
119
111.9
118.6
106.9
103.2
118.6
118.7
102.8
100.6
94.9
94.5
102.9
95.3
92.5
102.7
91.5
89.5
Dataseries Y:
Download CSV
Histogram 
37.2
37.2
34.7
32.5
33.5
31.5
31.2
27
26.7
26.5
26
27.2
30.5
33.7
34.2
36.7
36.2
38.5
40
42.5
43.5
43.3
45.5
44.3
43
43.5
41.5
42.5
41.3
39.5
38.5
41
44.5
46
44
41.5
41.3
38
38
36.2
38.7
38.7
39.2
35.7
36.5
36.7
34.7
35
28.2
23.7
15
8.7
11
7.5
5.7
9.3
10.2
15.7
18.1
20.8

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=56373&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=56373&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56373&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 axis3.64326647811823
y axis3.23165929492011
Correlation
correlation used in KDE0.581036051386541
correlation(x,y)0.581036051386541

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 3.64326647811823 \tabularnewline
y axis & 3.23165929492011 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.581036051386541 \tabularnewline
correlation(x,y) & 0.581036051386541 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56373&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]3.64326647811823[/C][/ROW]
[ROW][C]y axis[/C][C]3.23165929492011[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.581036051386541[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.581036051386541[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56373&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56373&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 axis3.64326647811823
y axis3.23165929492011
Correlation
correlation used in KDE0.581036051386541
correlation(x,y)0.581036051386541


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')