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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_tukeylambda.wasp
Title produced by softwareTukey lambda PPCC Plot
Date of computationFri, 04 Nov 2011 09:35:16 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/04/t13204137225gmawm3gvqcejer.htm/, Retrieved Tue, 16 Apr 2024 23:35:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=139633, Retrieved Tue, 16 Apr 2024 23:35:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact123

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Tukey lambda PPCC Plot] [] [2011-11-04 13:35:16] [204816f6f70a8d342ddc2b9d4f4a80d3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
-1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
1	'WWE'
1	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'WWE'
0	'CSWE'
-1	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
0	'CSWE'
0	'CSWE'
0	'CSWE'
1	'CSWE'
1	'CSWE'
0	'C'
0	'C'
-1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
1	'C'
0	'C'
0	'C'
0	'C'
1	'C'
1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
1	'C'
0	'C'
1	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'
0	'C'

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=139633&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=139633&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=139633&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 time0 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
gp <- function(lambda, p)
{
(p^lambda-(1-p)^lambda)/lambda
}
sortx <- sort(x)
c <- array(NA,dim=c(201))
for (i in 1:201)
{
if (i != 101) c[i] <- cor(gp(ppoints(x), lambda=(i-101)/100),sortx)
}
bitmap(file='test1.png')
plot((-100:100)/100,c[1:201],xlab='lambda',ylab='correlation',main='PPCC Plot - Tukey lambda')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Lambda - Key Values',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Distribution (lambda)',1,TRUE)
a<-table.element(a,'Correlation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Approx. Cauchy (lambda=-1)',header=TRUE)
a<-table.element(a,c[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Exact Logistic (lambda=0)',header=TRUE)
a<-table.element(a,(c[100]+c[102])/2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Approx. Normal (lambda=0.14)',header=TRUE)
a<-table.element(a,c[115])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'U-shaped (lambda=0.5)',header=TRUE)
a<-table.element(a,c[151])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Exactly Uniform (lambda=1)',header=TRUE)
a<-table.element(a,c[201])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')