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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 computationFri, 15 Dec 2017 11:42:47 +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/15/t1513334684oqoejhtd8g6dw5g.htm/, Retrieved Thu, 16 May 2024 00:43:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=309641, Retrieved Thu, 16 May 2024 00:43:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

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 ...] [2017-12-15 10:42:47] [f44dd4af88e8b85f25b182ab83c3a44e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
36.43
38.72
49.66
37.7
34.72
51.52
32.26
51.88
50.13
144.69
159.08
146.64
121.21
116.45
117.19
133.82
136.98
121.07
90.99
91.51
116.48
120.43
125.72
114.31
116.63
157.88
115.46
152.5
147.38
147.38
127.7
129.52
120.51
114.97
116.23
117.8
146.61
148.85
114.77
127.83
153.35
154.94
148.37
152.96
161.02
154.34
144.24
178.7
121.86
150.66
196.75
250.12
228.32
238.36
198.25
324.08
431.54
267.83
331.21
248.52
367.71
320.22
51.87
51.3
69.23
57.51
58.3
55.8
68.21
66.63
49.41
49.34
49.02
50.24
49.81
49.25
49.25
49.81
49.25
49.34
48.54
44.97
52.31
53.5
52.35
65.47
68
66.05
62.11
114.06
97.89
112.57
112.42
118.16
129.41
120.64
326.84
328.86
332.35
296.16
89.47
100.05
93.24
92.74
113.08
113.8
83.81
113.16
81.89
97.53
89.43
88.18
87.7
91.17
113.59
116.72
115.92
118.11
114.45
115.78
Dataseries Y:
Download CSV
Histogram 
2
-1
-3
-3
1
-3
2
2
-2
-3
1
-1
1
2
2
2
-2
3
3
3
2
0
0
1
1
-3
3
1
-2
-2
2
1
2
3
3
2
2
0
0
3
1
0
3
1
3
-1
-2
2
2
2
0
-1
-3
1
0
-1
-1
0
-2
0
-1
-2
-1
-1
2
3
3
3
0
3
0
0
0
0
0
0
0
0
-1
-1
-1
-2
-2
2
2
3
3
1
2
2
1
2
3
1
0
-2
-2
-1
-1
0
3
2
0
1
-2
-2
2
1
1
0
3
3
3
3
2
3
3
3
3
3

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=309641&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=309641&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309641&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 axis14.885322339755
y axis0.56228845966804
Correlation
correlation used in KDE-0.259072377121424
correlation(x,y)-0.259072377121424

\begin{tabular}{lllllllll}
\hline
Bandwidth \tabularnewline
x axis & 14.885322339755 \tabularnewline
y axis & 0.56228845966804 \tabularnewline
Correlation \tabularnewline
correlation used in KDE & -0.259072377121424 \tabularnewline
correlation(x,y) & -0.259072377121424 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=309641&T=1

[TABLE]
[ROW][C]Bandwidth[/C][/ROW]
[ROW][C]x axis[/C][C]14.885322339755[/C][/ROW]
[ROW][C]y axis[/C][C]0.56228845966804[/C][/ROW]
[ROW][C]Correlation[/C][/ROW]
[ROW][C]correlation used in KDE[/C][C]-0.259072377121424[/C][/ROW]
[ROW][C]correlation(x,y)[/C][C]-0.259072377121424[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=309641&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=309641&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 axis14.885322339755
y axis0.56228845966804
Correlation
correlation used in KDE-0.259072377121424
correlation(x,y)-0.259072377121424


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 = N ; par8 = terrain.colors ;
R code (references can be found in the software module):
par8 <- 'heat.colors'
par7 <- 'N'
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')