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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, 15 Dec 2014 17:35:55 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t14186649735bdkiitz2r0oake.htm/, Retrieved Thu, 16 May 2024 23:42:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268790, Retrieved Thu, 16 May 2024 23:42:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Cronbach Alpha] [] [2014-12-14 22:25:21] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D  [Cronbach Alpha] [] [2014-12-14 23:28:38] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMPD    [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 13:26:13] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D      [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 14:08:02] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM          [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 14:08:41] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D          [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 16:14:57] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP             [Percentiles] [] [2014-12-15 16:22:39] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                [Tukey lambda PPCC Plot] [] [2014-12-15 16:26:30] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                 [Kernel Density Estimation] [] [2014-12-15 16:30:20] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                   [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 16:35:22] [2b9d0c54c8c845c625e475ed5f1f3af1]
- R  D                    [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 17:24:27] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RMP                       [Percentiles] [] [2014-12-15 17:27:50] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                          [Percentiles] [] [2014-12-15 17:28:11] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                              [Tukey lambda PPCC Plot] [] [2014-12-15 17:35:55] [b22ed12f8980e34362f6926e9ebd1315] [Current]
- RM                                [Kernel Density Estimation] [] [2014-12-15 17:40:21] [2b9d0c54c8c845c625e475ed5f1f3af1]
-                                     [Kernel Density Estimation] [] [2014-12-15 17:42:13] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                  [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 17:47:00] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                                      [Percentiles] [] [2014-12-15 17:50:51] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                                        [Tukey lambda PPCC Plot] [] [2014-12-15 17:56:56] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM                                        [Kernel Density Estimation] [] [2014-12-15 18:08:51] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Maximum-likelihood Fitting - Normal Distribution] [] [2014-12-15 18:36:43] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Percentiles] [] [2014-12-15 18:50:26] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                        [Tukey lambda PPCC Plot] [] [2014-12-15 18:51:10] [2b9d0c54c8c845c625e475ed5f1f3af1]
- RM D                                          [Notched Boxplots] [] [2014-12-15 19:44:02] [2b9d0c54c8c845c625e475ed5f1f3af1]
-    D                                        [Kernel Density Estimation] [] [2014-12-15 18:53:06] [2b9d0c54c8c845c625e475ed5f1f3af1]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\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 & 0 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268790&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268790&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268790&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 time0 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Tukey Lambda - Key Values
Distribution (lambda)Correlation
Approx. Cauchy (lambda=-1)0.486125378406956
Exact Logistic (lambda=0)0.977406364871921
Approx. Normal (lambda=0.14)0.980387043814821
U-shaped (lambda=0.5)0.969987132799104
Exactly Uniform (lambda=1)0.956004862481421

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.486125378406956 \tabularnewline
Exact Logistic (lambda=0) & 0.977406364871921 \tabularnewline
Approx. Normal (lambda=0.14) & 0.980387043814821 \tabularnewline
U-shaped (lambda=0.5) & 0.969987132799104 \tabularnewline
Exactly Uniform (lambda=1) & 0.956004862481421 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268790&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]0.486125378406956[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.977406364871921[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.980387043814821[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.969987132799104[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.956004862481421[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268790&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268790&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)0.486125378406956
Exact Logistic (lambda=0)0.977406364871921
Approx. Normal (lambda=0.14)0.980387043814821
U-shaped (lambda=0.5)0.969987132799104
Exactly Uniform (lambda=1)0.956004862481421


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')