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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 computationTue, 11 Nov 2008 07:19:10 -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/t12264131909sls98te403x9zz.htm/, Retrieved Sun, 19 May 2024 09:38:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23507, Retrieved Sun, 19 May 2024 09:38:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Notched Boxplots] [workshop 3] [2007-10-26 13:31:48] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F RMPD  [Mean Plot] [workshop 4 deel 1...] [2008-10-31 09:40:26] [077ffec662d24c06be4c491541a44245]
F         [Mean Plot] [] [2008-11-01 13:19:15] [4c8dfb519edec2da3492d7e6be9a5685]
F    D      [Mean Plot] [] [2008-11-01 14:24:03] [4c8dfb519edec2da3492d7e6be9a5685]
F RMPD        [Star Plot] [Star Plot - Bob L...] [2008-11-02 16:44:14] [57850c80fd59ccfb28f882be994e814e]
F RMPD            [Trivariate Scatterplots] [Q1-3] [2008-11-11 14:19:10] [541f63fa3157af9df10fc4d202b2a90b] [Current]
Feedback Forum
2008-11-22 11:12:05 [Kenny Simons] [reply] 
Bij de trivariate scatterplots moet je opletten met de kubussen, deze zorgen altijd voor vertekening omdat deze driedimensionaal zijn. Je kan namelijk niet goed zien hoe de afstanden tussen de punten zich verhouden. Hierdoor is het beter te gaan zien naar de tweedimensionale scatterplots. Hieruit kan je beter aflezen of er een relatie is tussen bepaalde tijdreeksen of niet.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.5
98.8
106.2
98.3
102.1
117.1
101.5
80.5
105.9
109.5
97.2
114.5
93.5
100.9
121.1
116.5
109.3
118.1
108.3
105.4
116.2
111.2
105.8
122.7
99.5
107.9
124.6
115
110.3
132.7
99.7
96.5
118.7
112.9
130.5
137.9
115
116.8
140.9
120.7
134.2
147.3
112.4
107.1
128.4
137.7
135
151
137.4
132.4
161.3
139.8
146
166.5
143.3
121
152.6
154.4
154.6
158
Dataseries Y:
Download CSV
Histogram 
81.6
84.1
88.1
85.3
82.9
84.8
71.2
68.9
94.3
97.6
85.6
91.9
75.8
79.8
99
88.5
86.7
97.9
94.3
72.9
91.8
93.2
86.5
98.9
77.2
79.4
90.4
81.4
85.8
103.6
73.6
75.7
99.2
88.7
94.6
98.7
84.2
87.7
103.3
88.2
93.4
106.3
73.1
78.6
101.6
101.4
98.5
99
89.5
83.5
97.4
87.8
90.4
101.6
80
81.7
96.4
110.2
101.1
89.3
Dataseries Z:
Download CSV
Histogram 
91.2
99.2
108.2
101.5
106.9
104.4
77.9
60
99.5
95
105.6
102.5
93.3
97.3
127
111.7
96.4
133
72.2
95.8
124.1
127.6
110.7
104.6
112.7
115.3
139.4
119
97.4
154
81.5
88.8
127.7
105.1
114.9
106.4
104.5
121.6
141.4
99
126.7
134.1
81.3
88.6
132.7
132.9
134.4
103.7
119.7
115
132.9
108.5
113.9
142
97.7
92.2
128.8
134.9
128.2
114.8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23507&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23507&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23507&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 time5 seconds
R Server'George Udny Yule' @ 72.249.76.132


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Variable X ; par6 = Variable Y ; par7 = Variable Z ;
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))
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()