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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 computationFri, 30 Oct 2009 08:19:10 -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/30/t1256912405vhgnjha5oa57jns.htm/, Retrieved Mon, 29 Apr 2024 00:25:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52112, Retrieved Mon, 29 Apr 2024 00:25:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact202
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [] [2009-10-13 19:25:20] [ff6896cd60d3b2257a9a5027c462fa18]
-   PD  [Univariate Data Series] [SHWW2-Series2] [2009-10-13 19:36:05] [ff6896cd60d3b2257a9a5027c462fa18]
-    D    [Univariate Data Series] [sHWW2-Series3] [2009-10-13 19:44:51] [ff6896cd60d3b2257a9a5027c462fa18]
- RMPD        [Trivariate Scatterplots] [SHWW5-1] [2009-10-30 14:19:10] [be285953263a374c1f072a85fb5ca13a] [Current]
- RM D          [Partial Correlation] [SHWW5-2] [2009-10-30 14:26:59] [ff6896cd60d3b2257a9a5027c462fa18]
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Dataseries X:
2.9
2.6
2.3
2.3
2.6
3.1
2.8
2.5
2.9
3.1
3.1
3.2
2.5
2.6
2.9
2.6
2.4
1.7
2
2.2
1.9
1.6
1.6
1.2
1.2
1.5
1.6
1.7
1.8
1.8
1.8
1.3
1.3
1.4
1.1
1.5
2.2
2.9
3.1
3.5
3.6
4.4
4.2
5.2
5.8
5.9
5.4
5.5
4.7
3.1
2.6
2.3
1.9
0.6
0.6
-0.4
-1.1
-1.7
-0.8
-1.2
Dataseries Y:
108.8
128.4
121.1
119.5
128.7
108.7
105.5
119.8
111.3
110.6
120.1
97.5
107.7
127.3
117.2
119.8
116.2
111
112.4
130.6
109.1
118.8
123.9
101.6
112.8
128
129.6
125.8
119.5
115.7
113.6
129.7
112
116.8
127
112.1
114.2
121.1
131.6
125
120.4
117.7
117.5
120.6
127.5
112.3
124.5
115.2
104.7
130.9
129.2
113.5
125.6
107.6
107
121.6
110.7
106.3
118.6
104.6
Dataseries Z:
103.5
102.8
118.72
119.01
118.61
120.43
111.83
116.79
131.71
120.57
117.83
130.8
107.46
112.09
129.47
119.72
134.81
135.8
129.27
126.94
153.45
121.86
133.47
135.34
117.1
120.65
132.49
137.6
138.69
125.53
133.09
129.08
145.94
129.07
139.69
142.09
137.29
127.03
137.25
156.87
150.89
139.14
158.3
149
158.36
168.06
153.38
173.86
162.47
145.17
168.89
166.64
140.07
128.84
123.41
120.3
129.67
118.1
113.91
131.09




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52112&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]5 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=52112&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52112&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Productie consumptiegoederen ; par6 = Inflatie ; par7 = Import consumtiegoederen ;
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()