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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, 24 Oct 2008 11:27:20 -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/2008/Oct/24/t1224869309cva6cnqpd8lr8c8.htm/, Retrieved Tue, 29 Sep 2026 01:13:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18656, Retrieved Tue, 29 Sep 2026 01:13:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact518

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Tukey lambda PPCC Plot] [Investigating Dis...] [2007-10-21 16:01:20] [b9964c45117f7aac638ab9056d451faa]
F    D  [Tukey lambda PPCC Plot] [Associating Distr...] [2008-10-24 16:19:53] [a57f5cc542637534b8bb5bcb4d37eab1]
F    D      [Tukey lambda PPCC Plot] [Investigating Dis...] [2008-10-24 17:27:20] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
Feedback Forum
2008-10-29 13:46:25 [Ellen Smolders] [reply] 
De student heeft deze vraag juist beantwoord.
2008-10-30 22:27:30 [Kenny Simons] [reply] 
De student heeft deze vraag inderdaad juist opgelost, maar merk wel op dat we hier niet te maken hebben met een normaalverdeling, want dan moest de maximale correlatie liggen bij lambda = 0.14
2008-11-03 10:47:37 [Zeno Thoelen] [reply] 
2008-11-03 10:47:49 [a7e076854c32462fd499d2de3f6d4e86] [reply] 
Correcte oplossing

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
106,60
106,80
107,00
107,10
107,30
107,40
107,60
107,70
107,90
108,20
108,30
108,50
108,92
109,23
109,41
109,65
109,91
110,01
110,20
110,49
110,57
110,72
110,94
111,09
111,28
111,41
111,62
111,76
111,89
112,04
112,12
112,30
112,47
112,59
112,78
112,73
112,99
113,10
113,33
113,38
113,68
113,65
113,81
113,88
114,02
114,25
114,28
114,38
114,73
114,97
115,05
115,29
115,37
115,54
115,76
115,92
116,02
116,21
116,26
116,51

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18656&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]1 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=18656&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18656&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.596629984673256
Exact Logistic (lambda=0)0.966420168239148
Approx. Normal (lambda=0.14)0.981058054725727
U-shaped (lambda=0.5)0.995120949683193
Exactly Uniform (lambda=1)0.996202120306176

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.596629984673256 \tabularnewline
Exact Logistic (lambda=0) & 0.966420168239148 \tabularnewline
Approx. Normal (lambda=0.14) & 0.981058054725727 \tabularnewline
U-shaped (lambda=0.5) & 0.995120949683193 \tabularnewline
Exactly Uniform (lambda=1) & 0.996202120306176 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18656&T=1

[TABLE]
[ROW][C]Tukey Lambda - Key Values[/C][/ROW]
[ROW][C]Distribution (lambda)[/C][C]Correlation[/C][/ROW]
[ROW][C]Approx. Cauchy (lambda=-1)[/C][C]0.596629984673256[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.966420168239148[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.981058054725727[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.995120949683193[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.996202120306176[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18656&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18656&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.596629984673256
Exact Logistic (lambda=0)0.966420168239148
Approx. Normal (lambda=0.14)0.981058054725727
U-shaped (lambda=0.5)0.995120949683193
Exactly Uniform (lambda=1)0.996202120306176


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')