FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationMon, 27 Oct 2008 04:51:40 -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/27/t1225104864qw58lmz5hjbbj5p.htm/, Retrieved Sun, 19 May 2024 00:25:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19214, Retrieved Sun, 19 May 2024 00:25:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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...] [2007-10-22 19:59:15] [b9964c45117f7aac638ab9056d451faa]
F   PD    [Tukey lambda PPCC Plot] [q8 werkloosheid m...] [2008-10-27 10:51:40] [f24298b2e4c2a19d76cf4460ec5d2246] [Current]
Feedback Forum
2008-11-03 16:36:23 [Lindsay Heyndrickx] [reply] 
Hier is niet de hoogste correlatie bij lambda=14 dus het is hier niet de beste normaalverdeling maar er is nog steeds een goede normaalverdeling want een afwijking mag.
2008-11-03 20:38:48 [Jeroen Aerts] [reply] 
Een juiste normaalverdeling vinden we bij Lambda= 0.5 met 0.986226577043238
2008-11-03 22:38:45 [Nick Wuyts] [reply] 
Hier ga ik akkoord met de studente, een afwijking mag, het moet niet per se de beste normaalverdeling zijn.

voor additionele feedback die ik gegeven heb over lambda verwijs ik graag naar volgende link.

http://www.freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225103016c8e6kcu8dpckqr8.htm/

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7,8
7,6
7,5
7,6
7,5
7,3
7,6
7,5
7,6
7,9
7,9
8,1
8,2
8,0
7,5
6,8
6,5
6,6
7,6
8,0
8,0
7,7
7,5
7,6
7,7
7,9
7,8
7,5
7,5
7,1
7,5
7,5
7,6
7,7
7,7
7,9
8,1
8,2
8,2
8,1
7,9
7,3
6,9
6,6
6,7
6,9
7,0
7,1
7,2
7,1
6,9
7,0
6,8
6,4
6,7
6,7
6,4
6,3
6,2
6,5
6,8
6,8
6,5
6,3
5,9
5,9
6,4
6,4

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=19214&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=19214&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19214&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)0.59979594115861
Exact Logistic (lambda=0)0.963314462603482
Approx. Normal (lambda=0.14)0.97583334213503
U-shaped (lambda=0.5)0.986226577043238
Exactly Uniform (lambda=1)0.985596037597757

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.59979594115861 \tabularnewline
Exact Logistic (lambda=0) & 0.963314462603482 \tabularnewline
Approx. Normal (lambda=0.14) & 0.97583334213503 \tabularnewline
U-shaped (lambda=0.5) & 0.986226577043238 \tabularnewline
Exactly Uniform (lambda=1) & 0.985596037597757 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19214&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]0.59979594115861[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.963314462603482[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.97583334213503[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.986226577043238[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.985596037597757[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19214&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19214&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)0.59979594115861
Exact Logistic (lambda=0)0.963314462603482
Approx. Normal (lambda=0.14)0.97583334213503
U-shaped (lambda=0.5)0.986226577043238
Exactly Uniform (lambda=1)0.985596037597757


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 0 ;
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')