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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 computationSun, 26 Oct 2008 14:23:16 -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/26/t1225052899dulizyvjgk6nsvg.htm/, Retrieved Sun, 19 May 2024 13:37:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19054, Retrieved Sun, 19 May 2024 13:37:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact125

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] [Tukey Random Comp] [2008-10-26 20:23:16] [21d7d81e7693ad6dde5aadefb1046611] [Current]
Feedback Forum
2008-10-29 14:46:43 [Nathalie Koulouris] [reply] 
De student heeft gebruik gemaakt van de juiste methode, namelijk de Turkey Lambda PPCC Plot. We kunnen hier vaststellen dat de correlatiewaarde het hoogst is bij exact logistics.
2008-10-31 14:20:12 [Matthieu Blondeau] [reply] 
Dit is correct.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
338,3622951
617,8622951
261,8622951
490,1622951
546,8622951
389,5622951
441,5622951
346,5622951
393,1622951
567,3622951
461,7622951
531,1622951
486,9622951
495,9622951
347,6622951
493,1622951
550,3622951
470,7622951
414,0622951
470,4622951
371,1622951
535,8622951
506,2622951
631,2622951
526,0622951
560,7622951
400,7622951
640,5622951
605,3622951
624,9622951
473,1622951
567,5622951
449,5622951
605,5622951
485,5622951
739,4622951
415,1622951
571,2622951
408,6622951
540,2622951
594,1622951
423,7622951
425,5622951
416,5622951
534,0622951
757,6622951
467,4622951
609,2622951
504,1622951
739,6622951
716,2622951
476,8622951
708,1622951
556,2622951
507,1622951
484,8622951
441,9622951
423,9622951
386,7622951
354,6622951
195,8622951

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19054&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19054&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19054&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'George Udny Yule' @ 72.249.76.132






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.731408571341401
Exact Logistic (lambda=0)0.992200037856586
Approx. Normal (lambda=0.14)0.992102503257452
U-shaped (lambda=0.5)0.980018881027058
Exactly Uniform (lambda=1)0.965422281504803

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.731408571341401 \tabularnewline
Exact Logistic (lambda=0) & 0.992200037856586 \tabularnewline
Approx. Normal (lambda=0.14) & 0.992102503257452 \tabularnewline
U-shaped (lambda=0.5) & 0.980018881027058 \tabularnewline
Exactly Uniform (lambda=1) & 0.965422281504803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19054&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]0.731408571341401[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.992200037856586[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.992102503257452[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.980018881027058[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.965422281504803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19054&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19054&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)0.731408571341401
Exact Logistic (lambda=0)0.992200037856586
Approx. Normal (lambda=0.14)0.992102503257452
U-shaped (lambda=0.5)0.980018881027058
Exactly Uniform (lambda=1)0.965422281504803


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')