Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_cloud.wasp
Title produced by softwareTrivariate Scatterplots
Date of computationMon, 03 Dec 2007 03:18:28 -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/2007/Dec/03/t11966764448ghwc2ci0ys0jlb.htm/, Retrieved Fri, 03 May 2024 16:20:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2301, Retrieved Fri, 03 May 2024 16:20:44 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsex012008
Estimated Impact383
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Trivariate Scatterplots] [omzet, aantal en ...] [2007-12-03 10:18:28] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
589
606
566
487
442
463
547
432
513
602
637
913
576
634
563
513
483
477
524
470
427
537
662
1079
816
705
653
584
508
446
604
446
512
533
791
1206
783
567
473
412
314
323
438
429
468
518
555
816
673
593
569
505
447
433
549
553
505
601
706
852
643
448
551
476
416
331
435
395
405
619
596
889
668
555
620
472
460
417
582
525
507
750
899
1075
993
777
675
655
535
491
686
637
652
794
859
1049
1022
762
762
563
573
473
527
710
630
706
870
1069
1021
799
694
521
622
614
661
630
Dataseries Y:
122302.01
109264.65
103674.75
103890.3
75512.66
83121.3
125096.81
74206.73
88481.63
111598.17
146919.48
150790.85
113780.5
110870.76
118785.32
112820.5
102188.92
97092.73
114067.82
89690.15
89267.9
96198.64
129599.75
169424.7
152510.91
121850.2
144737.64
121381.88
106894.86
94305.06
116800.42
77584.28
100680.88
106634.05
168390.77
211971.89
136163.28
168950.25
89816.88
85406.93
66055.52
73311.68
85674.51
82822.59
94277.63
100991.65
149245.88
208517.17
40733.51
121352.23
104020.11
99566.82
101352.17
106628.41
109696.95
248696.37
105628.33
120449.17
136547.7
140896.42
131509.91
95450.31
133592.64
110332.9
88110.54
64931.25
98446.22
84212.38
77519.55
124806.02
102185.94
151348.79
124378.28
101433.13
126724.22
87461.88
95288.27
129055.33
107753.06
96364.03
71662.75
125666.24
456841.51
167642.32
167154.73
139685.18
119275.2
122746.05
107337.43
112584.89
133183.08
121152.57
119815.6
122858.44
152077.17
157221.96
140435.08
101455.09
104791.29
77226.59
84477.43
66227.74
89076.23
108924.43
83926.11
91764.8
120892.76
129952.42
135865.14
105512.77
96486.62
78064.88
92370.22
98454.46
96703.93
83170.95
Dataseries Z:
100.01
100.73
100.46
100.99
100.8
101.24
101.05
101.11
100.86
100.92
101.43
101.55
101.49
101.11
100.43
99.79
99.09
99.69
100.08
99.53
99.58
99.41
99.5
100.42
99.9
100.02
99.92
99.55
99.74
99.76
99.86
99.75
99.92
99.86
99.66
99.5
99.28
99.6
100.15
100.28
100.44
100.3
100.87
100.45
100.64
100.13
99.9
100.11
99.14
99.79
100.31
100.43
100.92
101.48
101.64
102.41
102.74
102.77
102.37
102
102.45
102.51
102.34
102.55
102.25
102.56
102.8
103.09
102.65
103.29
104
104.01
103.59
103.59
103.84
103.61
103.76
104.12
103.95
104.03
104.52
104.79
104.91
105.1
105.22
105.64
105.2
105.19
105.23
105.22
105.65
105.93
105.65
106.55
107.44
107.74
107.44
108.2
108.86
108.82
108.37
108.35
107.61
107.98
107.8
107.44
107.46
107.18
107.75
108.28
108.64
108.52
108.58
108.09
108.68
109.18




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2301&T=0

[TABLE]
[ROW][C]Summary of compuational 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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2301&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2301&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = aantal ; par6 = omzet ; par7 = koers ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = aantal ; par6 = omzet ; par7 = koers ;
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()