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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 computationSat, 05 Mar 2022 07:32:36 +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/2022/Mar/05/t1646461959a3e9ek2h8bojpai.htm/, Retrieved Tue, 14 May 2024 20:30:57 +0200
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=, Retrieved Tue, 14 May 2024 20:30:57 +0200
QR Codes:

Original text written by user:555
IsPrivate?No (this computation is public)
User-defined keywords555
Estimated Impact0

Tree of Dependent Computations

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
70.80
69.60
69.87
67.47
67.60
67.13
66.27
66.73
68.07
67.80
64.80
64.60
64.20
64.20
63.67
61.00
59.67
59.67
59.80
60.73
59.40
58.07
57.47
66.67
66.33
64.33
64.00
63.33
61.33
64.67
63.00
60.67
63.67
60.67
61.67
62.33
60.33
59.67
60.33
59.33
58.67
58.67
59.33
57.33
59.33
56.00
53.67
58.67
49.33
70.73
72.87
66.00
66.07
66.00
66.27
64.00
63.67
63.73
63.33
63.53
63.53
62.87
59.53
62.80
60.80
59.80
56.67
57.67
58.40
55.47
56.20
71.33
70.33
69.00
66.00
66.00
63.33
65.33
64.33
64.00
61.67
63.67
64.67
61.67
62.00
61.33
63.67
61.33
62.33
59.67
59.33
61.67
58.67
58.00
56.67
59.67
58.00
57.00
57.67
58.67
55.33
56.00
55.67
53.33
53.67
51.00
47.00
4.33
71.53
68.67
65.67
66.73
67.33
66.73
66.87
65.80
64.73
65.47
63.60
64.07
64.67
63.73
62.53
61.93
62.67
62.80
61.33
62.60
59.13
61.27
59.47
57.87
59.73
61.40
58.80
58.33
57.47
57.13
55.00
51.53
70.00
68.67
67.67
66.00
65.67
65.67
63.67
63.67
64.00
62.00
62.00
61.67
61.67
63.33
61.00
62.33
60.33
60.33
60.67
57.67
58.33
58.00
57.33
56.67
58.00
55.33
55.67
54.67
56.33
55.00
55.00
54.67
54.33
49.00
48.33
49.67
43.67
6.33
3.00
72.73
73.00
70.80
70.07
71.67
71.07
70.67
70.73
70.73
68.60
69.60
66.47
67.07
68.67
66.93
65.93
68.87
66.53
65.80
66.60
66.00
65.00
66.80
65.60
66.00
65.67
64.67
65.07
64.67
65.07
65.20
64.87
63.47
62.60
64.07
63.73
64.67
61.60
61.60
60.47
61.27
63.00
61.47
60.87
61.67
62.87
62.40
59.73
60.13
58.80
59.60
58.93
60.13
58.20
58.27
58.27
55.07
53.87
52.33
47.20
37.93
66.67
67.33
65.33
66.00
65.67
66.67
65.67
65.00
64.67
66.67
63.67
63.33
63.67
63.33
63.67
63.00
61.67
61.33
60.67
60.00
61.67
61.33
58.67
60.33
59.67
59.33
59.67
61.00
61.00
60.00
60.00
58.67
58.33
58.00
56.33
54.67
55.33
54.00
52.67
44.00
72.73
70.07
70.67
72.07
68.80
68.80
67.47
66.73
66.53
66.00
67.60
66.00
66.00
66.53
65.80
64.27
64.67
64.60
64.13
65.47
62.93
63.53
62.13
63.87
64.67
63.33
63.13
62.80
62.40
62.40
62.60
61.47
62.20
63.00
61.80
59.73
60.33
60.13
59.53
59.00
55.93
41.87
36.33
65.67
65.00
66.33
64.00
62.33
61.33
63.00
63.67
62.00
61.33
64.67
62.67
64.00
61.00
60.67
59.67
60.33
56.67
56.67
54.33
51.00
51.00
47.00
71.67
71.47
70.47
69.53
70.73
69.93
68.73
67.53
64.40
66.20
66.20
63.07
64.27
65.00
63.67
62.67
64.67
64.67
64.47
61.93
63.27
62.93
61.93
64.07
61.40
62.00
62.60
62.40
61.60
59.87
63.20
62.40
60.40
61.87
59.13
59.53
57.80
57.67
61.00
56.33
54.20
54.73
52.67
17.60
68
65
64
64
64
62
61
60
60
62
60
59
61
60
60
58
58
60
58
59
56
54
51
47
Dataseries Y:
Download CSV
Histogram 
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
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1
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1
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Tables (Output of Computation)





Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 time0 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=&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]0 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=&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 time0 seconds
R ServerBig Analytics Cloud Computing Center


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 1 ; par4 = 0 ; par5 = -1' OR 2+474-474-1=0+0+0+1 or 'fWn26Dss'=' ; par6 = 1 ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = 1 ; par7 = 1 ; par8 = 1 ;
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')