Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationMon, 05 Nov 2007 02:48:08 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/05/pwdnzir8gx1h58p1194256024.htm/, Retrieved Sun, 28 Apr 2024 20:23:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=512, Retrieved Sun, 28 Apr 2024 20:23:51 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ1, Trivariate Scatterplots
Estimated Impact194
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Trivariate Scatterplots] [Q1 Trivariate Sca...] [2007-11-05 09:48:08] [1dd4e56f2879fe34e71a5ad240ab3149] [Current]
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Dataseries X:
95,90
96,06
96,31
96,34
96,49
96,22
96,53
96,50
96,77
96,66
96,58
96,63
97,06
97,73
98,01
97,76
97,49
97,77
97,96
98,23
98,51
98,19
98,37
98,31
98,60
98,97
99,11
99,64
100,03
99,98
100,32
100,44
100,51
101,00
100,88
100,55
100,83
101,51
102,16
102,39
102,54
102,85
103,47
103,57
103,69
103,50
103,47
103,45
103,48
103,93
103,89
104,40
104,79
104,77
105,13
105,26
104,96
104,75
105,01
105,15
105,20
105,77
105,78
106,26
106,13
106,12
106,57
106,44
106,54
Dataseries Y:
2,90
2,63
2,67
1,81
1,33
0,88
1,28
1,26
1,26
1,29
1,10
1,37
1,21
1,74
1,76
1,48
1,04
1,62
1,49
1,79
1,80
1,58
1,86
1,74
1,59
1,26
1,13
1,92
2,61
2,26
2,41
2,26
2,03
2,86
2,55
2,27
2,26
2,57
3,07
2,76
2,51
2,87
3,14
3,11
3,16
2,47
2,57
2,89
2,63
2,38
1,69
1,96
2,19
1,87
1,60
1,63
1,22
1,21
1,49
1,64
1,66
1,77
1,82
1,78
1,28
1,29
1,37
1,12
1,51
Dataseries Z:
96,92
96,06
96,59
96,67
97,27
96,38
96,47
96,05
96,76
96,51
96,55
95,97
97,00
97,46
97,90
98,42
98,54
99,00
98,94
99,02
100,07
98,72
98,73
98,04
99,08
99,22
99,57
100,44
100,84
100,75
100,49
99,98
99,96
99,76
100,11
99,79
100,29
101,12
102,65
102,71
103,39
102,80
102,07
102,15
101,21
101,27
101,86
101,65
101,94
102,62
102,71
103,39
104,51
104,09
104,29
104,57
105,39
105,15
106,13
105,46
106,47
106,62
106,52
108,04
107,15
107,32
107,76
107,26
107,89




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=512&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=512&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Alg. Indexcijfe ; par6 = Kledingproducti ; par7 = Voeding ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Alg. Indexcijfe ; par6 = Kledingproducti ; par7 = Voeding ;
R code (references can be found in the software module):
x <- array(x,dim=c(length(x),1))
colnames(x) <- par5
y <- array(y,dim=c(length(y),1))
colnames(y) <- par6
z <- array(z,dim=c(length(z),1))
colnames(z) <- par7
d <- data.frame(cbind(z,y,x))
colnames(d) <- list(par7,par6,par5)
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
if (par1>500) par1 <- 500
if (par2>500) par2 <- 500
if (par1<10) par1 <- 10
if (par2<10) par2 <- 10
library(GenKern)
library(lattice)
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='black', ...)
}
bitmap(file='cloud1.png')
cloud(z~x*y, screen = list(x=-45, y=45, z=35),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='cloud2.png')
cloud(z~x*y, screen = list(x=35, y=45, z=25),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='cloud3.png')
cloud(z~x*y, screen = list(x=35, y=-25, z=90),xlab=par5,ylab=par6,zlab=par7)
dev.off()
bitmap(file='pairs.png')
pairs(d,diag.panel=panel.hist)
dev.off()
x <- as.vector(x)
y <- as.vector(y)
z <- as.vector(z)
bitmap(file='bidensity1.png')
op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=cor(x,y), xbandwidth=dpik(x), ybandwidth=dpik(y))
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,y)',xlab=par5,ylab=par6)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(x,y)
(r<-lm(y ~ x))
abline(r)
box()
dev.off()
bitmap(file='bidensity2.png')
op <- KernSur(y,z, xgridsize=par1, ygridsize=par2, correlation=cor(y,z), xbandwidth=dpik(y), ybandwidth=dpik(z))
op
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (y,z)',xlab=par6,ylab=par7)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(y,z)
(r<-lm(z ~ y))
abline(r)
box()
dev.off()
bitmap(file='bidensity3.png')
op <- KernSur(x,z, xgridsize=par1, ygridsize=par2, correlation=cor(x,z), xbandwidth=dpik(x), ybandwidth=dpik(z))
op
image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main='Bivariate Kernel Density Plot (x,z)',xlab=par5,ylab=par7)
if (par3=='Y') contour(op$xords, op$yords, op$zden, add=TRUE)
if (par4=='Y') points(x,z)
(r<-lm(z ~ x))
abline(r)
box()
dev.off()