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Author's title

Author*Unverified author*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationMon, 08 Dec 2008 14:31:12 -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/2008/Dec/08/t1228771968de6xhpbn91ji1eq.htm/, Retrieved Thu, 16 May 2024 05:28:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31069, Retrieved Thu, 16 May 2024 05:28:48 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords372papertrideplotind&inv&con
Estimated Impact147
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Trivariate Scatterplots] [papertrideplotind...] [2008-12-08 21:31:12] [d8c5724db236abb5950452133b88474d] [Current]
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Dataseries X:
99.1
98.6
100.4
100.7
101.3
100.1
100.4
99.5
101.5
100.2
99.7
98.9
100.6
99.8
99.4
100.5
98.9
99.9
102
99.5
100
100.2
99.3
100.9
100.8
103.1
101.5
101.3
100
101.2
103.8
104.2
103.8
104.4
101.8
102
100.6
99.3
94.3
101.8
100.2
103.4
102.9
100.8
103.5
99.6
104.9
104.7
104.4
104.2
104.7
104.4
107.9
105.9
104.8
105.9
107
108.6
106.8
110
108.9
108.8
109.1
108.7
108.7
109
109.2
109.7
108.1
109.4
110.1
107.8
Dataseries Y:
107.4
103.8
103.5
106.6
111
110.1
109.1
108.3
99.5
115.6
90.6
92.9
102
102.7
97.9
102.6
106.7
101.9
103.4
91.2
94.6
91.7
98.8
104.4
100.3
104.2
105.7
108.7
100.2
104.2
101.4
105.4
105.4
111.5
104
103.6
108.4
107.1
108.2
109.2
102.6
108.1
112.8
108.1
110.4
102.7
108.2
109.3
111.2
113.5
114.3
108.6
121.3
116.1
113.1
113
117.4
121.2
121
122
123.1
120.7
123.5
125.8
124.3
130.5
129.2
124.6
128.9
127.8
128.6
132.7
Dataseries Z:
103.5
103.6
103.6
103.2
103.4
101.9
103.8
102
101
103.7
101.1
99.3
115.4
111.9
109
112.8
104.6
106.1
110.7
109.9
112.3
112.5
111.3
113.8
110.2
112
115.2
113.1
110.8
117.3
117.7
115.5
115.2
112.8
115.8
119.3
119.4
113.2
115.4
115.1
115.3
113.3
110.8
113.8
114.8
111.1
112.9
112
118.5
120.1
119.6
118
120.4
118.2
117.5
118.6
119.2
119.9
118.9
118.3
120.3
120.4
119.4
119.1
119.3
119.4
131.4
118.6
116.4
118.8
118.2
116.5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31069&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]2 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=31069&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31069&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 computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Totale industrie ; par6 = Investeringsgoederen ; par7 = Consumptiegoederen ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Totale industrie ; par6 = Investeringsgoederen ; par7 = Consumptiegoederen ;
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()