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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_boxcoxnorm.wasp
Title produced by softwareBox-Cox Normality Plot
Date of computationTue, 11 Nov 2008 09:37:50 -0700
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/Nov/11/t122642148909ihw781z16qnu4.htm/, Retrieved Mon, 20 May 2024 07:28:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23698, Retrieved Mon, 20 May 2024 07:28:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Box-Cox Normality Plot] [Various EDA topic...] [2008-11-11 16:37:50] [db9a5fd0f9c3e1245d8075d8bb09236d] [Current]
F RMP     [Maximum-likelihood Fitting - Normal Distribution] [Various EDA topic...] [2008-11-11 16:40:54] [d134696a922d84037f02d49ded84b0bd]
F RMPD    [Partial Correlation] [Various EDA topic...] [2008-11-11 16:42:24] [d134696a922d84037f02d49ded84b0bd]
Feedback Forum
2008-11-24 10:18:05 [Stijn Van de Velde] [reply] 
Bij deze methode gaan we kijken of er een lambda bestaat zodanig dat je de x-variabele kan transformeren om een lineair verband te maken van de scatterplot. Deze lambda wordt diegene met de grootste correlatie, dus waar de grafiek een maximum bereikt.

Hier kan je zien dat er een maximum word bereikt, namelijk bij lambda = -0.78

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3219.2
3552.3
3787.7
3392.7
3550
3681.9
3519.1
4283.2
4046.2
3824.9
4793.1
3977.7
3983.4
4152.9
4286.1
4348.1
3949.3
4166.7
4217.9
4528.2
4232.2
4470.9
5121.2
4170.8
4398.6
4491.4
4251.8
4901.9
4745.2
4666.9
4210.4
5273.6
4095.3
4610.1
4718.1
4185.5
4314.7
4422.6
5059.2
5043.6
4436.6
4922.6
4454.8
5058.7
4768.9
5171.8
4989.3
5202.1
4838.4
4876.5
5845.3
5686.3
4753.8
6620.4
5597.2
5643.5
6357.3
5909.1
6165.8
6321.6

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'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23698&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23698&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23698&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'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Box-Cox Normality Plot
# observations x60
maximum correlation0.896188803168625
optimal lambda-0.78

\begin{tabular}{lllllllll}
\hline
Box-Cox Normality Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.896188803168625 \tabularnewline
optimal lambda & -0.78 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23698&T=1

[TABLE]
[ROW][C]Box-Cox Normality Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]60[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.896188803168625[/C][/ROW]
[ROW][C]optimal lambda[/C][C]-0.78[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23698&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23698&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:

Box-Cox Normality Plot
# observations x60
maximum correlation0.896188803168625
optimal lambda-0.78


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
R code (references can be found in the software module):
n <- length(x)
c <- array(NA,dim=c(401))
l <- array(NA,dim=c(401))
mx <- 0
mxli <- -999
for (i in 1:401)
{
l[i] <- (i-201)/100
if (l[i] != 0)
{
x1 <- (x^l[i] - 1) / l[i]
} else {
x1 <- log(x)
}
c[i] <- cor(qnorm(ppoints(x), mean=0, sd=1),x1)
if (mx < c[i])
{
mx <- c[i]
mxli <- l[i]
}
}
c
mx
mxli
if (mxli != 0)
{
x1 <- (x^mxli - 1) / mxli
} else {
x1 <- log(x)
}
bitmap(file='test1.png')
plot(l,c,main='Box-Cox Normality Plot',xlab='Lambda',ylab='correlation')
mtext(paste('Optimal Lambda =',mxli))
grid()
dev.off()
bitmap(file='test2.png')
hist(x,main='Histogram of Original Data',xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test3.png')
hist(x1,main='Histogram of Transformed Data',xlab='X',ylab='frequency')
grid()
dev.off()
bitmap(file='test4.png')
qqnorm(x)
qqline(x)
grid()
mtext('Original Data')
dev.off()
bitmap(file='test5.png')
qqnorm(x1)
qqline(x1)
grid()
mtext('Transformed Data')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Box-Cox Normality Plot',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations x',header=TRUE)
a<-table.element(a,n)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum correlation',header=TRUE)
a<-table.element(a,mx)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'optimal lambda',header=TRUE)
a<-table.element(a,mxli)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')