FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 07 Dec 2016 15:48:39 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Dec/07/t148112215644pvqg59588k28l.htm/, Retrieved Fri, 01 Nov 2024 03:33:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=298167, Retrieved Fri, 01 Nov 2024 03:33:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

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 ...] [2016-12-07 14:48:39] [7b02c9ca65294818d9c418453f92ae83] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1
2
2
2
1
2
2
2
1
1
1
1
1
1
1
2
1
2
2
2
1
2
2
1
1
1
1
1
1
1
2
1
1
2
1
1
2
1
1
2
2
2
2
2
2
2
2
2
1
2
1
2
2
1
2
1
1
2
1
2
2
2
2
1
2
1
2
1
2
2
2
2
1
2
1
2
1
2
2
1
1
1
2
2
2
2
2
1
2
1
1
1
1
2
2
2
1
2
2
1
1
2
2
2
2
1
1
1
2
2
2
1
1
2
1
1
2
1
1
1
2
2
2
2
2
1
1
2
2
2
1
2
1
1
1
2
1
1
1
1
2
1
2
2
2
2
1
1
1
1
2
2
2
2
1
2
1
2
1
1
1
1
1
2
2
1
Dataseries Y:
Download CSV
Histogram 
13
13
12
15
12
12
12
10
9
15
14
11
18
14
11
9
16
15
14
17
13
11
13
10
13
14
10
15
12
10
10
14
12
15
13
10
14
11
11
12
13
14
13
14
13
11
19
13
13
15
11
16
13
15
13
9
12
14
15
11
12
14
13
14
10
14
14
16
16
14
14
11
4
14
14
9
11
11
10
12
11
8
9
13
16
14
13
14
13
19
11
8
14
11
14
12
7
14
13
14
11
9
14
10
15
13
16
14
14
15
16
16
12
8
12
14
13
9
10
13
12
11
12
12
14
10
10
14
9
13
11
15
11
12
17
12
12
10
13
11
13
11
13
11
13
10
14
13
16
8
15
16
12
15
13
13
18
8
12
8
13
16
16
15
12
11

Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time1 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298167&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]1 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=298167&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298167&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R ServerBig Analytics Cloud Computing Center






Bandwidth
x axis0.0397948415999853
y axis0.872881375652678
Correlation
correlation used in KDE0.0884036742522709
correlation(x,y)0.0884036742522709

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.0397948415999853 \tabularnewline
y axis & 0.872881375652678 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.0884036742522709 \tabularnewline
correlation(x,y) & 0.0884036742522709 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=298167&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.0397948415999853[/C][/ROW]
[ROW][C]y axis[/C][C]0.872881375652678[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.0884036742522709[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.0884036742522709[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=298167&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=298167&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 axis0.0397948415999853
y axis0.872881375652678
Correlation
correlation used in KDE0.0884036742522709
correlation(x,y)0.0884036742522709


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):
par8 <- 'terrain.colors'
par7 <- 'Y'
par6 <- 'Y'
par5 <- '0'
par4 <- '0'
par3 <- '0'
par2 <- '50'
par1 <- '50'
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')