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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_tukeylambda.wasp
Title produced by softwareTukey lambda PPCC Plot
Date of computationSun, 26 Oct 2008 09:14:57 -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/t12250349714e5mcltj32mw1jg.htm/, Retrieved Sat, 18 May 2024 05:47:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18933, Retrieved Sat, 18 May 2024 05:47:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact150

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] [Q8 distributions] [2008-10-25 19:29:29] [547636b63517c1c2916a747d66b36ebf]
F    D    [Tukey lambda PPCC Plot] [Q9 Tukey lamda] [2008-10-26 15:14:57] [17f1768efd19cdd5063f8ba074ce8995] [Current]
Feedback Forum
2008-11-03 21:24:32 [Bonifer Spillemaeckers] [reply] 
We zien hier inderdaad dat de grootste correlatie ligt bij lambda = 0,14. De grootste correlatie vinden we dus met andere woorden bij de normaalverdeling.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
15859,4
15258,9
15498,6
15106,5
15023,6
12083
15761,3
16942,6
15070,3
13659,6
14768,9
14725,1
15998,1
15370,6
14956,9
15469,7
15101,8
11703,7
16283,6
16726,5
14968,9
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17422
16704,5
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22238,5
20682,2
17818,6
21872,1
22117
21865,9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18933&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18933&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18933&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.660769602923188
Exact Logistic (lambda=0)0.984586417821317
Approx. Normal (lambda=0.14)0.989976469676735
U-shaped (lambda=0.5)0.98738840471055
Exactly Uniform (lambda=1)0.978848371063683

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.660769602923188 \tabularnewline
Exact Logistic (lambda=0) & 0.984586417821317 \tabularnewline
Approx. Normal (lambda=0.14) & 0.989976469676735 \tabularnewline
U-shaped (lambda=0.5) & 0.98738840471055 \tabularnewline
Exactly Uniform (lambda=1) & 0.978848371063683 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18933&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]0.660769602923188[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.984586417821317[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.989976469676735[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.98738840471055[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.978848371063683[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18933&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18933&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)0.660769602923188
Exact Logistic (lambda=0)0.984586417821317
Approx. Normal (lambda=0.14)0.989976469676735
U-shaped (lambda=0.5)0.98738840471055
Exactly Uniform (lambda=1)0.978848371063683


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')