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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 computationThu, 29 Oct 2009 10:20:09 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/29/t1256833303pctt34d6k6obfqq.htm/, Retrieved Mon, 29 Apr 2024 05:41:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52015, Retrieved Mon, 29 Apr 2024 05:41:07 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Trivariate Scatterplots] [workshop 5] [2009-10-29 16:20:09] [6198946fb53eb5eb18db46bb758f7fde] [Current]
-  MPD    [Trivariate Scatterplots] [Workshop 5 xyz] [2009-11-03 20:27:02] [616e2df490b611f6cb7080068870ecbd]
- RMP       [Partial Correlation] [WS5 Partial Corre...] [2009-11-03 20:34:59] [616e2df490b611f6cb7080068870ecbd]
- RMPD        [Bivariate Explorative Data Analysis] [WS5 Bivariate EDA] [2009-11-03 21:05:09] [616e2df490b611f6cb7080068870ecbd]
-    D          [Bivariate Explorative Data Analysis] [Workshop 5 Bivari...] [2009-11-03 21:45:54] [616e2df490b611f6cb7080068870ecbd]
-    D            [Bivariate Explorative Data Analysis] [WS5 Bivariate EDA...] [2009-11-03 21:59:14] [616e2df490b611f6cb7080068870ecbd]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.5291
1.5358
1.5355
1.5287
1.5334
1.5225
1.5135
1.5144
1.4913
1.4793
1.4663
1.4749
1.4745
1.4775
1.4678
1.4658
1.4572
1.4721
1.4624
1.4636
1.4649
1.465
1.4673
1.4679
1.4621
1.4674
1.4695
1.4964
1.5155
1.5411
1.5476
1.54
1.5474
1.5485
1.559
1.5544
1.5657
1.5734
1.567
1.5547
1.54
1.5192
1.527
1.5387
1.5431
1.5426
1.5216
1.5364
1.5469
1.5501
1.5494
1.5475
1.5448
1.5391
1.5578
1.5528
1.5496
1.549
1.5449
1.5479
Dataseries Y:
Download CSV
Histogram 
0.6348
0.634
0.62915
0.62168
0.61328
0.6089
0.60857
0.62672
0.62291
0.62393
0.61838
0.62012
0.61659
0.6116
0.61573
0.61407
0.62823
0.64405
0.6387
0.63633
0.63059
0.62994
0.63709
0.64217
0.65711
0.66977
0.68255
0.68902
0.71322
0.70224
0.70045
0.69919
0.69693
0.69763
0.69278
0.70196
0.69215
0.6769
0.67124
0.66532
0.67157
0.66428
0.66576
0.66942
0.6813
0.69144
0.69862
0.695
0.69867
0.68968
0.69233
0.68293
0.68399
0.66895
0.68756
0.68527
0.6776
0.68137
0.67933
0.67922
Dataseries Z:
Download CSV
Histogram 
1.6891
1.7236
1.8072
1.7847
1.6813
1.6469
1.689
1.7169
1.8036
1.7955
1.7172
1.7348
1.7094
1.6963
1.6695
1.6537
1.6662
1.6793
1.7922
1.8045
1.7927
1.7831
1.7847
1.8076
1.8218
1.8112
1.795
1.7813
1.7866
1.7552
1.7184
1.7114
1.6967
1.6867
1.6337
1.6626
1.6374
1.626
1.637
1.6142
1.7033
1.7483
1.7135
1.7147
1.7396
1.7049
1.6867
1.7462
1.7147
1.667
1.6806
1.6738
1.6571
1.5875
1.6002
1.6144
1.6009
1.5937
1.603
1.5979

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52015&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52015&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52015&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Zwitserse frank tov de Euro ; par6 = Britse pond tov de Euro ; par7 = Australische dollar tov de Euro ;
Parameters (R input):
par1 = 50 ; par2 = 50 ; par3 = Y ; par4 = Y ; par5 = Zwitserse frank tov de Euro ; par6 = Britse pond tov de Euro ; par7 = Australische dollar tov de Euro ;
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()