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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, 15 Dec 2014 20:47:37 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418676533p7hhuwdluieqlax.htm/, Retrieved Thu, 16 May 2024 08:18:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269025, Retrieved Thu, 16 May 2024 08:18:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact42

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2014-12-15 20:47:37] [ca907db95fc0b179b22bb0898c34dff4] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
30
17
24
20
25
20
27
18
28
21
27
22
28
25
21
22
28
20
29
20
20
23
18
18
19
25
25
25
24
19
26
10
17
13
17
30
4
16
21
22
20
22
23
16
0
18
25
18
18
24
29
15
22
23
24
22
15
17
20
27
26
23
23
15
26
22
18
15
22
27
10
20
17
23
19
13
27
23
16
25
2
26
20
22
24
23
22
21
25
27
23
23
18
18
23
19
15
20
16
25
25
19
19
16
19
19
23
21
22
19
20
3
23
14
23
20
15
13
16
7
24
17
24
24
19
28
23
19
23
25
25
20
16
20
25
25
23
17
20
16
23
12
24
11
14
23
18
29
16
19
16
23
19
4
20
20
4
24
16
3
24
23
17
20
22
19
24
19
27
22
23
Dataseries Y:
Download CSV
Histogram 
16.6
12.6
18.9
11.6
14.6
13.85
14.85
11.75
18.45
15.9
19.9
10.95
18.45
15.1
15
11.35
15.95
18.1
14.6
17.6
15.35
13.4
13.9
15.25
12.9
16.1
17.35
13.15
12.15
12.6
10.35
15.4
9.6
18.2
13.6
14.85
14.1
14.9
16.25
13.6
15.65
14.6
12.65
11.9
19.2
16.6
11.2
13.2
15.85
11.15
15.65
7.65
15.2
15.6
13.1
11.85
12.4
11.4
14.9
19.9
11.2
14.6
14.75
15.15
16.85
7.85
12.6
7.85
10.95
12.35
9.95
14.9
16.65
13.4
13.95
15.7
16.85
10.95
15.35
12.2
15.1
17.75
15.2
16.65
8.1
4.35
12.7
18.1
17.85
17.1
19.1
16.1
13.35
18.4
14.7
10.6
12.6
16.2
13.6
14.1
14.5
16.15
14.75
14.8
12.45
12.65
17.35
8.6
18.4
16.1
17.75
15.25
17.65
15.6
16.35
17.65
13.6
11.7
14.35
14.75
18.25
9.9
16
18.25
16.85
18.95
15.6
17.1
16.1
15.4
15.4
13.35
19.1
7.6
19.1
14.75
19.25
13.6
12.75
9.85
15.25
11.9
16.35
12.4
14.35
18.15
17.75
12.35
15.6
19.3
17.1
18.4
19.05
18.55
19.1
12.85
9.5
4.5
13.6
11.7
13.35
17.75
17.6
14.05
16.1
13.35
11.85
11.95
13.2
7.7
14.6

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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\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 & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269025&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269025&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269025&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'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Bandwidth
x axis1.60312902964584
y axis1.06159951126883
Correlation
correlation used in KDE0.112013750398079
correlation(x,y)0.112013750398079

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.60312902964584 \tabularnewline
y axis & 1.06159951126883 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.112013750398079 \tabularnewline
correlation(x,y) & 0.112013750398079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269025&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.60312902964584[/C][/ROW]
[ROW][C]y axis[/C][C]1.06159951126883[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.112013750398079[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.112013750398079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269025&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269025&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 axis1.60312902964584
y axis1.06159951126883
Correlation
correlation used in KDE0.112013750398079
correlation(x,y)0.112013750398079


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ; par8 = terrain.colors ;
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')
x <- x[!is.na(y)]
y <- y[!is.na(y)]
y <- y[!is.na(x)]
x <- x[!is.na(x)]
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
if (par8 == 'terrain.colors') mycol <- terrain.colors(100)
if (par8 == 'rainbow') mycol <- rainbow(100)
if (par8 == 'heat.colors') mycol <- heat.colors(100)
if (par8 == 'topo.colors') mycol <- topo.colors(100)
if (par8 == 'cm.colors') mycol <- cm.colors(100)
bitmap(file='bidensity.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=par5, xbandwidth=par3, ybandwidth=par4)
image(op$xords, op$yords, op$zden, col=mycol, axes=TRUE,main=main,xlab=xlab,ylab=ylab)
if (par6=='Y') contour(op$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')