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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 2014 23:03:23 +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/18/t1418943861j01joci3rknd8lm.htm/, Retrieved Sun, 19 May 2024 20:25:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271316, Retrieved Sun, 19 May 2024 20:25:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact81

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Reddy Moores Boxp...] [2010-10-12 16:37:57] [98fd0e87c3eb04e0cc2efde01dbafab6]
- R P   [Boxplot and Trimmed Means] [Reddy-Moores Plac...] [2010-10-13 09:46:26] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMPD    [Notched Boxplots] [] [2010-10-15 11:13:23] [b98453cac15ba1066b407e146608df68]
- RMPD      [Testing Mean with unknown Variance - Critical Value] [I1 hypo] [2014-12-18 22:46:45] [0f2441473984dd788bd8148394ed78a8]
- R  D        [Testing Mean with unknown Variance - Critical Value] [I2 hypo] [2014-12-18 22:51:24] [0f2441473984dd788bd8148394ed78a8]
- RM D            [Bivariate Kernel Density Estimation] [Ext motivatie kernal] [2014-12-18 23:03:23] [8aa9b0b9e9cdf95f84c1d02ac9593640] [Current]
- R  D              [Bivariate Kernel Density Estimation] [E2 num] [2014-12-18 23:08:44] [0f2441473984dd788bd8148394ed78a8]
- R  D              [Bivariate Kernel Density Estimation] [E2 num] [2014-12-18 23:08:44] [0f2441473984dd788bd8148394ed78a8]
-    D                [Bivariate Kernel Density Estimation] [I3 hypo] [2014-12-18 23:11:52] [0f2441473984dd788bd8148394ed78a8]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21
26
22
22
18
23
12
20
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15
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9
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10
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15
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3
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14
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13
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7
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28
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12
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14
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18
29
16
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16
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4
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4
24
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3
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23
28
29
21
24
20
7
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28
26
19
20
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16
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24
21
16
16
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NA
28
16
23
26
29
18
19
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16
16
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14
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16
15
11
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NA
19
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11
23
27
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26
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16
Dataseries Y:
Download CSV
Histogram 
18
23
23
22
22
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25
28
16
28
21
22
24
24
26
28
20
26
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27
23
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5
24
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14
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17
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21
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20
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16
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15
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10
24
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24
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21
23
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23
22
27
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24
20
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21
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21
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21
28
25
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18
14
25
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27
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11
25
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25
28
18
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28
21
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15
27
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19
19
28

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271316&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271316&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271316&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'George Udny Yule' @ yule.wessa.net






Bandwidth
x axis1.34582978817889
y axis0.863520817912309
Correlation
correlation used in KDE0.0169568408633365
correlation(x,y)0.0169568408633365

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 1.34582978817889 \tabularnewline
y axis & 0.863520817912309 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.0169568408633365 \tabularnewline
correlation(x,y) & 0.0169568408633365 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271316&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]1.34582978817889[/C][/ROW]
[ROW][C]y axis[/C][C]0.863520817912309[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.0169568408633365[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.0169568408633365[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271316&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271316&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 axis1.34582978817889
y axis0.863520817912309
Correlation
correlation used in KDE0.0169568408633365
correlation(x,y)0.0169568408633365


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 ; 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')