Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationThu, 06 Nov 2008 09:16:57 -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/06/t1225988243f1k555dgsw10onf.htm/, Retrieved Tue, 14 May 2024 13:58:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=22302, Retrieved Tue, 14 May 2024 13:58:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [trivariate ] [2007-11-05 10:19:55] [ede03b06b9ae6a59763c2cc70a5f12fe]
F    D    [Trivariate Scatterplots] [] [2008-11-06 16:16:57] [1b288879226ab9a3cab0c803857233cc] [Current]
Feedback Forum
2008-11-14 12:47:37 [Dana Molenberghs] [reply
Er is een duidelijke positieve correlatie tussen X en Z. Dit kan je zien op de bivariate kernel density. Bij Y en Z zien we 2 clusters. Bij de eerste zien we een stijgende positieve correlatie. Maar door de tweede cluster zal de correlatie afgezwakt worden, omdat je ziet dat deze hier daalt.
2008-11-24 21:53:07 [Niels Herremans] [reply
Bij de kubussen is het niet eenvoudig om een patroon te zien. In de kolom/grafiek daaronder kan je op de hoofdiagonaal het histogram aflezen en boven de hoofdiagonaal de scatterplot, dit is beter bruikbaar. Daaronder is er telkens de bivariate kernel denisty plot weer gegeven.

Post a new message
Dataseries X:
96,8
91,2
97,1
104,9
110,9
104,8
94,1
95,8
99,3
101,1
104,0
99,0
105,4
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145,0
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179,0
190,6
190,0
181,6
174,8
180,5
196,8
193,8
197,0
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244,0
234,7
250,2
Dataseries Y:
96,9
98,0
97,9
100,9
103,9
103,1
102,5
104,3
102,6
101,7
102,8
105,4
110,9
113,5
116,3
124,0
128,8
133,5
132,6
128,4
127,3
126,7
123,3
123,2
124,4
128,2
128,7
135,7
139,0
145,4
142,4
137,7
137,0
137,1
139,3
139,6
140,4
142,3
148,3
157,7
161,6
161,7
171,8
185,1
176,7
184,4
183,0
180,9
187,0
189,9
193,8
194,5
198,7
204,7
213,2
214,7
211,0
213,2
206,3
210,8
Dataseries Z:
96,7
88,0
96,7
106,8
114,3
105,7
90,1
91,6
97,7
100,8
104,6
95,9
102,7
104,0
107,9
113,8
113,8
123,1
125,1
137,6
134,0
140,3
152,1
150,6
167,3
153,2
142,0
154,4
158,5
180,9
181,3
172,4
192,0
199,3
215,4
214,3
201,5
190,5
196,0
215,7
209,4
214,1
237,8
239,0
237,8
251,5
248,8
215,4
201,2
203,1
214,2
188,9
203,0
213,3
228,5
228,2
240,9
258,8
248,5
269,2




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=22302&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=22302&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=22302&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = incl energie ; par6 = excl energie ; par7 = totaal ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = incl energie ; par6 = excl energie ; par7 = totaal ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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()