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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 computationMon, 27 Oct 2008 16:01:30 -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/t12251449284g1b8920sjwqtl2.htm/, Retrieved Fri, 17 May 2024 03:03:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19674, Retrieved Fri, 17 May 2024 03:03:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

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    D    [Tukey lambda PPCC Plot] [Tukey Lambda PPCC...] [2008-10-27 22:01:30] [d592f629d96b926609f311957d74fcca] [Current]
Feedback Forum
2008-10-29 16:11:26 [Jan Van Riet] [reply] 
Je conclusie klopt; bij lamba is 0 staat de maximumwaarde van 0.968399425020933.
Dit wil zeggen dat de tijdreeks volkomen uniform is (en dus niet gewoon maar de normaalverdeling heeft).
  2008-11-02 22:16:52 [Koen Van den Heuvel] [reply] 
Ik weet niet of we het over dezelfde grafiek hebben maar ik zie toch wel degelijk een maximum bij 'Exactly Uniform (lambda=1)' van 0.996285445155194. Een waarde hoger dan 968399425020933 bij 'Exact Logistic (lambda=0)'

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2120.88
2174.56
2196.72
2350.44
2440.25
2408.64
2472.81
2407.60
2454.62
2448.05
2497.84
2645.64
2756.76
2849.27
2921.44
2981.85
3080.58
3106.22
3119.31
3061.26
3097.31
3161.69
3257.16
3277.01
3295.32
3363.99
3494.17
3667.03
3813.06
3917.96
3895.51
3801.06
3570.12
3701.61
3862.27
3970.10
4138.52
4199.75
4290.89
4443.91
4502.64
4356.98
4591.27
4696.96
4621.40
4562.84
4202.52
4296.49
4435.23
4105.18
4116.68
3844.49
3720.98
3674.40
3857.62
3801.06
3504.37
3032.60
3047.03
2962.34

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=19674&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=19674&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19674&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)0.604730012598784
Exact Logistic (lambda=0)0.968399425020933
Approx. Normal (lambda=0.14)0.982411274738895
U-shaped (lambda=0.5)0.995546760337308
Exactly Uniform (lambda=1)0.996285445155194

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.604730012598784 \tabularnewline
Exact Logistic (lambda=0) & 0.968399425020933 \tabularnewline
Approx. Normal (lambda=0.14) & 0.982411274738895 \tabularnewline
U-shaped (lambda=0.5) & 0.995546760337308 \tabularnewline
Exactly Uniform (lambda=1) & 0.996285445155194 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19674&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]0.604730012598784[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.968399425020933[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.982411274738895[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.995546760337308[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.996285445155194[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19674&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19674&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)0.604730012598784
Exact Logistic (lambda=0)0.968399425020933
Approx. Normal (lambda=0.14)0.982411274738895
U-shaped (lambda=0.5)0.995546760337308
Exactly Uniform (lambda=1)0.996285445155194


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')