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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 computationMon, 12 Sep 2016 21:51:02 +0200
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2016/Sep/12/t1473709900fi9d7jgdrxryegf.htm/, Retrieved Thu, 31 Oct 2024 23:39:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=296523, Retrieved Thu, 31 Oct 2024 23:39:34 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact159
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2016-09-12 18:12:08] [597f04887712160a284bcf6998091a8a]
- RMPD    [Trivariate Scatterplots] [] [2016-09-12 19:51:02] [101a6ec9f938885df0a44f20458d2eb4] [Current]
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Dataseries X:
11
19
16
24
15
17
19
19
28
26
15
26
16
24
25
22
15
21
22
27
26
26
22
21
22
20
21
20
22
21
8
22
20
24
17
20
23
20
22
19
15
20
22
17
14
24
17
23
25
16
18
20
18
23
24
23
13
20
20
19
22
22
15
17
19
20
22
21
21
16
20
21
20
23
18
16
17
24
13
19
20
22
19
21
15
21
24
22
20
21
19
14
25
11
17
22
20
22
15
23
20
22
16
25
18
19
25
21
22
21
22
23
20
6
15
18
24
22
21
23
20
20
18
25
16
20
14
22
26
20
17
22
22
20
17
22
17
22
21
25
11
19
24
17
22
17
26
20
19
21
24
21
19
13
24
28
27
22
23
19
18
23
21
22
17
15
21
20
26
19
28
21
19
22
21
20
19
11
17
19
20
17
21
21
12
23
22
22
21
20
18
21
24
22
20
17
19
16
19
23
8
22
23
15
17
21
25
18
20
21
21
24
22
22
23
17
15
22
19
18
21
20
19
19
16
18
23
22
23
20
24
25
25
20
23
21
23
23
11
21
27
19
21
16
21
22
16
18
23
24
20
20
18
4
14
22
17
23
20
18
19
20
15
24
21
19
19
27
23
23
20
17
21
23
22
16
20
16
Dataseries Y:
8
18
12
24
16
19
16
15
28
21
18
22
19
22
25
20
16
19
18
26
24
20
19
19
23
18
16
18
21
20
15
19
19
7
20
20
19
19
20
18
14
17
17
8
9
22
20
20
22
22
22
16
14
24
21
20
20
18
14
19
24
19
16
16
16
14
22
21
15
14
15
14
20
21
14
16
13
26
13
18
15
18
21
17
18
20
18
25
20
19
18
12
22
16
18
23
20
20
16
22
19
23
6
19
24
19
15
18
18
22
23
18
17
6
22
20
16
16
17
20
23
18
13
22
20
20
13
16
25
16
15
19
19
24
9
22
15
22
22
24
12
21
25
26
21
14
28
21
16
16
25
21
22
9
20
19
24
22
22
12
17
18
10
22
24
18
18
23
21
21
28
17
21
21
20
18
17
7
17
14
18
14
23
20
14
17
21
23
24
21
14
24
16
21
8
17
18
17
16
22
17
21
20
20
19
8
19
11
13
18
19
23
20
22
19
16
11
21
14
21
20
21
20
19
19
18
20
21
22
19
23
16
23
18
23
20
20
23
13
21
26
18
19
18
18
19
13
10
21
24
21
23
18
11
16
20
20
26
21
12
15
18
14
18
16
19
7
21
24
21
20
22
17
19
20
16
20
16
Dataseries Z:
7
20
9
19
12
16
17
9
28
20
16
22
17
12
18
20
12
16
16
21
15
17
17
17
18
15
20
13
21
12
6
13
19
12
14
13
12
17
19
10
10
11
11
10
7
22
12
18
20
9
16
14
11
20
17
14
8
16
11
10
15
15
10
10
18
10
22
16
10
7
16
16
16
22
5
10
8
16
8
16
14
15
9
21
7
17
18
16
16
14
15
8
22
5
13
22
18
15
11
19
19
21
4
17
10
13
15
11
20
13
18
20
15
4
9
18
12
17
12
16
17
14
13
20
16
15
10
16
21
15
16
19
9
19
7
23
14
10
16
12
10
7
20
9
12
10
19
11
15
14
11
14
15
7
22
19
22
11
19
9
11
17
12
17
10
17
13
11
19
21
24
13
16
13
15
15
11
7
13
13
12
8
7
17
9
18
17
17
18
12
14
22
19
21
10
16
11
15
12
21
22
20
15
9
15
14
11
9
12
11
14
10
18
11
14
16
11
16
13
12
17
23
14
10
16
11
16
19
17
12
17
11
19
12
8
17
13
17
7
23
18
13
17
13
8
16
14
13
19
15
15
8
14
7
11
17
19
17
12
12
18
16
15
20
16
12
10
28
19
18
19
8
17
16
18
12
17
13




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=296523&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=296523&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=296523&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ; par4 = 0 ; par5 = 0 ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Variable X ; par6 = Variable Y ; par7 = Variable Z ;
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))
print(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))
print(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()