Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationWed, 12 Nov 2008 11:32:31 -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/12/t1226514897b8ymm49g4n64ykb.htm/, Retrieved Sun, 19 May 2024 09:10:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=24363, Retrieved Sun, 19 May 2024 09:10:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordstrivariate scatterplots
Estimated Impact206
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Partial Correlation] [] [2008-11-12 15:23:04] [b87cf4f6ac665e4d6a88fc8d9f2625f6]
F RMPD    [Trivariate Scatterplots] [trivariate scatte...] [2008-11-12 18:32:31] [35c75b0726318bf2908e4a56ed2df1a9] [Current]
Feedback Forum
2008-11-21 22:02:03 [Gilliam Schoorel] [reply
Spijtig dat je de drie dimensionale puntenwolken niet in je word doc hebt gezet. Zo kan je soms nieuwe verbanden ontdekken uit verschillende opzichten. Hier kan je duidelijk spreken van een neutraal correlatieverband. Je kan de bivariate density evt verder onerzoeken omdat er lichte vertekeningen kunnen ontstaan door de driedimensionale weergave/vervorming.
2008-11-24 15:21:40 [Ellen Van den Broeck] [reply
Er is geen duidelijke correlatie merkbaar in de scatterplots tussen de gegevens.

Post a new message
Dataseries X:
62.2
88.5
93.3
89.2
101.3
97
102.2
100.3
78.2
105.9
119.9
108
77
93.1
109.5
100.4
99
113.9
102.1
101.6
84
110.7
111.6
110.7
73.1
87.5
109.6
99.3
92.1
109.3
94.5
91.4
82.9
103.3
96
104.8
65.8
78.7
100.3
85
94.5
97.9
91.9
87.2
84.4
99.2
105.4
110.9
69.8
86.8
106.7
88.8
96.9
108.1
93.7
94.8
79.8
95.6
107.9
104.9
61.9
85.7
92.4
86.4
99.3
95.5
97
102.1
77.8
105.5
113.2
108.8
66.9
89.3
93.6
92
99.5
98.6
94.6
96.7
75.3
102.5
115.1
104.7
71.4
Dataseries Y:
43.5
37.7
36.8
24.4
31.3
43.9
53.6
48.9
30.9
31.8
41.3
43.7
54.1
47.8
36.7
30.8
31.9
61.7
73
64.7
24.2
33.9
32.4
63.2
71.8
60.4
48
44.5
44.9
70.9
72.7
59.5
35.9
40
43.6
57.2
75.8
57.7
47.7
42.3
43
68
70.6
54.2
38.6
40.3
49.2
68.5
75.9
63.2
49.8
37
48.8
74.9
75.3
66.9
44.1
39.8
56.6
77.1
78.5
70.6
54.2
47.2
55.1
74.5
88
80.8
54.4
55.2
73.8
85.3
98.7
86.1
62.5
58.6
67
88.4
96.5
87.1
61.2
62.5
85.2
101.7
113.7
Dataseries Z:
200.7
146.5
143.6
141.5
137.5
138.7
135.5
136.4
112.1
109
123.8
151.2
139.2
115.7
147.6
126.1
122.8
137.3
142
137.4
89.4
108
117.7
127.3
121
104.1
119.5
116.7
96.1
125
118.8
114.9
79.3
90.5
87.8
109.4
88.9
97.4
112
86.8
82.9
105.2
89.1
85.5
87.1
85.2
88.2
104
96.4
82.3
114.1
88.9
93.6
101.8
96.6
93.7
68.4
68.7
81.2
85.1
75.4
71.6
83
72.3
90.2
89
84.9
90.9
46.6
55.4
88.7
76
76.9
72.1
90
92.3
78
93.9
84.5
80.4
60.5
75.3
91.5
105.2
92.7




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=24363&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=24363&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=24363&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 = 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()