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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationTue, 11 Nov 2008 07:27:56 -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/Nov/11/t12264137202spknqvg0u3lhzm.htm/, Retrieved Sun, 19 May 2024 10:41:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23523, Retrieved Sun, 19 May 2024 10:41:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [Q1] [2008-11-11 14:12:08] [491a70d26f8c977398d8a0c1c87d3dd4]
F RMPD  [Partial Correlation] [Q2] [2008-11-11 14:20:55] [491a70d26f8c977398d8a0c1c87d3dd4]
F RMP       [Trivariate Scatterplots] [Q1] [2008-11-11 14:27:56] [2ba2a74112fb2c960057a572bf2825d3] [Current]
Feedback Forum
2008-11-24 23:04:52 [Liese Tormans] [reply
Aan de hand van de Trivariate Scatterplots is het niet eenvoudig een mooi patroon te vinden en een conclusie te trekken. Want de 3D voorstelling geeft een vertekend beeld op een 2D scherm. Daarnaast weet je niet hoe 3D zich uit tussen de afstand van de punten.

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Dataseries X:
109.6
103
111.6
106.3
97.9
108.8
103.9
101.2
122.9
123.9
111.7
120.9
99.6
103.3
119.4
106.5
101.9
124.6
106.5
107.8
127.4
120.1
118.5
127.7
107.7
104.5
118.8
110.3
109.6
119.1
96.5
106.7
126.3
116.2
118.8
115.2
110
111.4
129.6
108.1
117.8
122.9
100.6
111.8
127
128.6
124.8
118.5
114.7
112.6
128.7
111
115.8
126
111.1
113.2
120.1
130.6
124
119.4
116.7
Dataseries Y:
93.4
101.1
114.2
104.8
113.3
118.2
83.6
73.9
99.5
97.7
103
106.3
92.2
101.8
122.8
111.8
106.3
121.5
81.9
85.4
110.9
117.3
106.3
105.6
101.2
105.9
126.3
111.9
108.9
127.2
94.2
85.7
116.2
107.2
110.5
112
104.4
112
132.8
110.8
128.7
136.8
94.8
88.8
123.2
125.3
122.7
125.8
116.3
118.6
142.1
127.9
132
152.4
110.8
99.1
134.9
133.2
131
133.9
119.9
Dataseries Z:
97.6
99.5
110.7
104.4
99.8
108.4
91.8
90.2
109.2
111.4
102.8
91.5
98.9
100.8
112.1
106.7
103.5
111.3
100.8
94.2
115.5
114.1
105
94
98.3
96
101.8
102.5
98.7
110.7
88.7
89.2
106.8
104.1
103.2
93.7
100.5
98.7
111.1
104.5
105
109.7
92.6
94.2
111.7
113.4
106.8
98
104.2
105.4
117.5
107.9
107
113.3
97.6
98.2
111.3
116
108.1
95.6
110.8




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 4 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23523&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23523&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23523&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 time4 seconds
R Server'George Udny Yule' @ 72.249.76.132



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = totale consumptiegoederen ; par6 = investeringsgoederen ; par7 = intermediaire goederen ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = totale consumptiegoederen ; par6 = investeringsgoederen ; par7 = intermediaire goederen ;
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()