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Description of Statistical Computation

Author's title

Q8: Can you find a symmetric distribution that describes the random compone...

Author*Unverified author*
R Software Modulerwasp_tukeylambda.wasp
Title produced by softwareTukey lambda PPCC Plot
Date of computationMon, 27 Oct 2008 18:43:10 -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/28/t1225154672j45fv49zyb7wfz0.htm/, Retrieved Sun, 19 May 2024 20:26:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19727, Retrieved Sun, 19 May 2024 20:26:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

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] [Q8: Can you find ...] [2008-10-28 00:43:10] [1d70db93c36870279a28f714be132c6e] [Current]
Feedback Forum
2008-11-03 21:37:17 [Bonifer Spillemaeckers] [reply] 
We zien inderdaad dat de grootste correlatie te vinden is bij een lambdawaarde van 5. Dit komt overeen met een uniforme verdeling.



Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92,7
122,8
115,4
128,3
120,2
118,9
114,7
114,6
121,7
129,7
115,2
100,7
89,8
128,7
105,9
111,7
130,3
108
109,6
139
123,6
131
120,7
81,1
88,4
128,9
120,8
95
132
117,9
102,4
117,4
113,5
108
127,6
86,9
76,1
128,8
104,1
121,2
140,2
116
115
112,3
128,9
131,2
128,7
85,8
78,2
128,4
105,5
120,3
135,4
107,1
96,9
95,1
113,1
104,5
106,3
66,6
87,8
117,3
102,1
98,9
130,2
102,4
89,9
95,9
95,4
116,2
115,7
74,1
75,2
107,7
103,7
107,1
113,5
94,7
90,9
97
111
109,6
110,1
77,7
78
113,3
111,4
95,4
141,2
120,4
124,9
106,4
116,5
102,1
94,1
74
87

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=19727&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=19727&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19727&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)0.59578907431093
Exact Logistic (lambda=0)0.981556389983852
Approx. Normal (lambda=0.14)0.989633717627
U-shaped (lambda=0.5)0.99018063131428
Exactly Uniform (lambda=1)0.98260761282159

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.59578907431093 \tabularnewline
Exact Logistic (lambda=0) & 0.981556389983852 \tabularnewline
Approx. Normal (lambda=0.14) & 0.989633717627 \tabularnewline
U-shaped (lambda=0.5) & 0.99018063131428 \tabularnewline
Exactly Uniform (lambda=1) & 0.98260761282159 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19727&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]0.59578907431093[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.981556389983852[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.989633717627[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.99018063131428[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.98260761282159[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19727&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19727&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)0.59578907431093
Exact Logistic (lambda=0)0.981556389983852
Approx. Normal (lambda=0.14)0.989633717627
U-shaped (lambda=0.5)0.99018063131428
Exactly Uniform (lambda=1)0.98260761282159


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')