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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, 21 Dec 2017 10:59:09 +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/2017/Dec/21/t151385041096l8k2gruvb9yrz.htm/, Retrieved Wed, 22 May 2024 06:34:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=310598, Retrieved Wed, 22 May 2024 06:34:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsimproved water source vs. life expectancy
Estimated Impact92

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 ...] [2017-12-21 09:59:09] [97ca58e32232a99e44a6c848c7facc09] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
95,6
85,7
98,4
100
82,8
100
99,6
100
99,2
99,5
99,8
99,2
100
100
100
98,3
99,5
100
100
96,8
100
100
100
100
95,8
85,1
97,4
100
100
96,9
93,2
99
86,1
98,9
97,7
95
100
99,4
87,4
98,9
83,5
100
100
97,6
99,6
100
96,9
96,3
97
99,3
100
99,5
100
100
100
69,7
95,8
98,6
96,7
99,6
100
99,1
54,6
Dataseries Y:
Download CSV
Histogram 
76,74790244
74,66978049
73,10929268
80,5804878
70,91860976
76,15531707
70,40487805
80,18292683
75,79373171
73,51219512
81,19756098
76,47560976
79,38495122
77,42439024
79,1
70,34141463
75,42926829
79,87073171
81,66341463
72,49804878
79,98780488
80,38780488
74,20731707
81,89756098
73,95619512
68,48217073
80,74390244
81,60243902
82,03658537
73,43839024
68,29536585
74,13285366
69,3
73,48292683
78,53826829
73,26829268
80,63170732
74,60409756
69,51065854
75,20353659
73,94107317
80,70243902
80,99756098
76,24634146
79,02682927
77,6404878
73,45853659
68,84121951
73,70014634
74,33658537
75,11219512
79,42195122
81,62682927
81,45121951
82,24634146
69,80236585
74,81126829
74,09404878
70,26536585
76,69487805
80,40243902
78,54146341
63,4982439

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=310598&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=310598&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310598&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 axis0.674453570856908
y axis1.38648964293913
Correlation
correlation used in KDE0.638232025246009
correlation(x,y)0.638232025246009

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 0.674453570856908 \tabularnewline
y axis & 1.38648964293913 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & 0.638232025246009 \tabularnewline
correlation(x,y) & 0.638232025246009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=310598&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]0.674453570856908[/C][/ROW]
[ROW][C]y axis[/C][C]1.38648964293913[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]0.638232025246009[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]0.638232025246009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=310598&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=310598&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 axis0.674453570856908
y axis1.38648964293913
Correlation
correlation used in KDE0.638232025246009
correlation(x,y)0.638232025246009


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')