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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 computationSat, 25 Oct 2008 08:19:03 -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/25/t12249443988iikrpzz2jgompt.htm/, Retrieved Sun, 19 May 2024 02:42:51 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18747, Retrieved Sun, 19 May 2024 02:42:51 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsTurkey Lambda PPCC plot Uitvoer Amerika
Estimated Impact157

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] [Turkey Lambda PPC...] [2008-10-25 14:19:03] [8da7502cfecb272886bc60b3f290b8b8] [Current]
Feedback Forum
2008-11-04 07:37:51 [Koen De Winter] [reply] 
De correlatiecoëfficiënt is inderdaad het hoogst bij de logistic distribution. Moest de vraag zijn de beste distributie, dan was het hier aangewezen om de normale distributie te verkiezen. Dit model is eenvoudiger om mee te werken en er kan meer uit geanalyseerd worden.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1190.8
728.8
995.6
1260.3
994
957.3
975.6
884.9
908.4
1022.8
958.6
825.1
1116.6
724.2
1004.5
1058.9
854.7
943.4
792.4
873.2
1101.4
987.1
1038.8
1060.7
1047.7
840
1044
1097.4
987.5
934
977
881.1
1083.3
1074.7
1182.2
1117.5
1117.4
936.2
1246.3
1175.1
1177.7
1035.8
1091.6
998.7
1247.9
1034.7
1287.7
994.0
1122.8
1017.3
1106.0
1191.8
1030.1
989.4
979.6
1088.0
1389.2
1043.9
1182.1
1109.6
1463.3
1276.2
1082.4
1360.4
1130.2
1019.6
1077.0
958.8
959.6
907.2
880.8
759.6
1137.2

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=18747&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=18747&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18747&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)0.714958546351983
Exact Logistic (lambda=0)0.994364831097333
Approx. Normal (lambda=0.14)0.992536394050968
U-shaped (lambda=0.5)0.976382230512035
Exactly Uniform (lambda=1)0.958864739845422

\begin{tabular}{lllllllll}
\hline
Tukey Lambda - Key Values \tabularnewline
Distribution (lambda) & Correlation \tabularnewline
Approx. Cauchy (lambda=-1) & 0.714958546351983 \tabularnewline
Exact Logistic (lambda=0) & 0.994364831097333 \tabularnewline
Approx. Normal (lambda=0.14) & 0.992536394050968 \tabularnewline
U-shaped (lambda=0.5) & 0.976382230512035 \tabularnewline
Exactly Uniform (lambda=1) & 0.958864739845422 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18747&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]0.714958546351983[/C][/ROW]
[ROW][C]Exact Logistic (lambda=0)[/C][C]0.994364831097333[/C][/ROW]
[ROW][C]Approx. Normal (lambda=0.14)[/C][C]0.992536394050968[/C][/ROW]
[ROW][C]U-shaped (lambda=0.5)[/C][C]0.976382230512035[/C][/ROW]
[ROW][C]Exactly Uniform (lambda=1)[/C][C]0.958864739845422[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18747&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18747&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)0.714958546351983
Exact Logistic (lambda=0)0.994364831097333
Approx. Normal (lambda=0.14)0.992536394050968
U-shaped (lambda=0.5)0.976382230512035
Exactly Uniform (lambda=1)0.958864739845422


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')