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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationThu, 29 Oct 2009 08:00:50 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/29/t12568249569ktvo0jrzuo7zxy.htm/, Retrieved Mon, 29 Apr 2024 03:21:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51995, Retrieved Mon, 29 Apr 2024 03:21:31 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHWWS5 Trivariate Scatterplot werkloosheidsgraden man/vrouw, economische groei (Z)
Estimated Impact160

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Bivariate EDA ana...] [2009-10-27 11:17:50] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD      [Trivariate Scatterplots] [Trivariate Scatte...] [2009-10-29 14:00:50] [d1081bd6cdf1fed9ed45c42dbd523bf1] [Current]
- RMP         [Partial Correlation] [Partial Correlati...] [2009-10-29 14:05:54] [4395c69e961f9a13a0559fd2f0a72538]
- RMPD          [Bivariate Explorative Data Analysis] [Bivariate EDA Y[t] Z] [2009-10-29 14:14:40] [4395c69e961f9a13a0559fd2f0a72538]
-    D            [Bivariate Explorative Data Analysis] [Bivariate EDA Y[t...] [2009-10-29 15:03:23] [4395c69e961f9a13a0559fd2f0a72538]
-    D              [Bivariate Explorative Data Analysis] [Bivariate EDA X[t...] [2009-10-29 15:21:11] [4395c69e961f9a13a0559fd2f0a72538]
-    D                [Bivariate Explorative Data Analysis] [Bivariate EDA e[t...] [2009-10-29 15:36:56] [4395c69e961f9a13a0559fd2f0a72538]
-  M D                  [Bivariate Explorative Data Analysis] [Paper Bivariate E...] [2009-12-17 15:39:37] [4395c69e961f9a13a0559fd2f0a72538]
-  M D                [Bivariate Explorative Data Analysis] [Bivariate EDA X[t...] [2009-12-17 15:23:33] [4395c69e961f9a13a0559fd2f0a72538]
-  M D              [Bivariate Explorative Data Analysis] [Paper Bivariate E...] [2009-12-17 15:17:06] [4395c69e961f9a13a0559fd2f0a72538]
-    D          [Partial Correlation] [Partial Correlati...] [2009-10-29 14:50:04] [4395c69e961f9a13a0559fd2f0a72538]
-  M D            [Partial Correlation] [Paper Partial Cor...] [2009-12-17 15:11:15] [4395c69e961f9a13a0559fd2f0a72538]
-   PD        [Trivariate Scatterplots] [Trivariate Scatte...] [2009-10-29 14:46:49] [4395c69e961f9a13a0559fd2f0a72538]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.9
9.1
9.4
9.4
9.1
9
9.3
9.9
9.8
9.3
8.3
8
8.5
10.4
11.1
10.9
10
9.2
9.2
9.5
9.6
9.5
9.1
8.9
9
10.1
10.3
10.2
9.6
9.2
9.3
9.4
9.4
9.2
9
9
9
9.8
10
9.8
9.3
9
9
9.1
9.1
9.1
9.2
8.8
8.3
8.4
8.1
7.7
7.9
7.9
8
7.9
7.6
7.1
6.8
6.5
6.9
8.2
8.7
8.3
7.9
7.5
7.8
8.3
8.4
8.2
7.7
7.2
7.3
Dataseries Y:
Download CSV
Histogram 
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8
7.5
6.8
6.5
6.6
7.6
8
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
Dataseries Z:
Download CSV
Histogram 
-0.8
-0.2
0.2
1
0
-0.2
1
0.4
1
1.7
3.1
3.3
3.1
3.5
6
5.7
4.7
4.2
3.6
4.4
2.5
-0.6
-1.9
-1.9
0.7
-0.9
-1.7
-3.1
-2.1
0.2
1.2
3.8
4
6.6
5.3
7.6
4.7
6.6
4.4
4.6
6
4.8
4
2.7
3
4.1
4
2.7
2.6
3.1
4.4
3
2
1.3
1.5
1.3
3.2
1.8
3.3
1
2.4
0.4
-0.1
1.3
-1.1
-4.4
-7.5
-12.2
-14.5
-16
-16.7
-16.3
-16.9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 6 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51995&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51995&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51995&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 Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Werkloosheidsgraad vrouwen ; par6 = Werkloosheidsgraad mannen ; par7 = Economische groei ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Werkloosheidsgraad vrouwen ; par6 = Werkloosheidsgraad mannen ; par7 = Economische groei ;
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()