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Author*The author of this computation has been verified*
R Software Modulerwasp_boxcoxnorm.wasp
Title produced by softwareBox-Cox Normality Plot
Date of computationTue, 16 Dec 2014 12:02:57 +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/16/t1418731389by70nd0bylkwnia.htm/, Retrieved Thu, 16 May 2024 10:14:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269381, Retrieved Thu, 16 May 2024 10:14:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact54
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Box-Cox Normality Plot] [] [2014-12-16 12:02:57] [7de19aadd459682308988067914fc05d] [Current]
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Dataseries X:
11
15
19
16
24
15
17
19
19
28
26
15
26
16
24
25
22
15
21
22
27
26
26
22
21
22
20
21
20
22
21
8
22
18
20
24
17
20
23
20
22
19
15
20
22
17
14
24
17
23
25
16
18
20
18
23
24
23
13
20
20
19
22
22
15
17
19
20
22
21
21
16
20
21
20
23
15
18
22
16
17
24
13
19
20
22
19
21
15
21
24
22
20
21
19
14
25
11
17
22
20
22
15
23
20
22
16
25
18
19
25
21
22
21
22
23
20
6
15
18
24
22
21
23
20
20
18
25
16
20
14
22
26
20
17
22
22
20
17
22
17
22
21
25
11
19
24
17
22
22
17
26
19
20
19
21
24
21
19
13
24
28
27
22
23
19
18
23
21
22
17
15
21
20
26
19
28
21
19
22
21
20
19
11
17
19
20
17
21
21
12
23
22
22
21
20
18
21
24
22
20
17
19
16
19
23
8
22
23
15
17
21
25
18
23
20
21
21
24
22
22
23
17
15
24
22
19
18
21
20
19
19
16
18
23
22
23
20
24
25
25
20
23
21
23
23
11
21
27
19
21
16
22
21
22
16
18
23
24
20
20
18
4
14
22
17
23
20
18
19
20
15
24
21
19
19
27
23
23
20
17
21
23
22
16
20
16
21
19
27
13
17
18
20
22
18
6
22
15
19
17
22
10
21
21
23
18
20
27
13
20
20
22
20
24
23
19
22
24
21
19
20
16
17
25
16
23
20
23
22
15
16
20
23
24
17
19
25
14
18
22
15
27
22
26
16
25
20
19
19
24
14
18
13
19
25
20
17
17
13
20
20
24
25
19
20
20
22
18
21
20
11
18
22
21
15
23
18
23
19
23
26
19
26
20
20
23
24
26
23
19
25
23
19
27
23
24
20
16
22
26
26
24
20
20
12
21
27
26
17
20
18
28
24
24
24
12
26
23
13
23
16
23
18
25
18
18
21
7
19
21
17
22
15
20
19
10
18
25
23
25
23
21
23
19
22
23
15
23
23
24
20
23
24
17
21
19
23
22
14
19
21
23
16
23
19
19
22
26
22
24
24
11
21
21
22
22
19
18
19
27
14
15
20
22
26
20
13
26
19
20
18
20
21
26
25
20
21




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' @ fisher.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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269381&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' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269381&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269381&T=0

As an alternative you can also use a 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' @ fisher.wessa.net







Box-Cox Normality Plot
# observations x498
maximum correlation0.0671120583815167
optimal lambda2

\begin{tabular}{lllllllll}
\hline
Box-Cox Normality Plot \tabularnewline
# observations x & 498 \tabularnewline
maximum correlation & 0.0671120583815167 \tabularnewline
optimal lambda & 2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269381&T=1

[TABLE]
[ROW][C]Box-Cox Normality Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]498[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.0671120583815167[/C][/ROW]
[ROW][C]optimal lambda[/C][C]2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269381&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269381&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Box-Cox Normality Plot
# observations x498
maximum correlation0.0671120583815167
optimal lambda2



Parameters (Session):
par1 = 1 ; par2 = 80 ; par3 = 1e-08 ;
Parameters (R input):
par1 = Full Box-Cox transform ; par2 = -2 ; par3 = 2 ; par4 = 0 ; par5 = No ;
R code (references can be found in the software module):
par2 <- abs(as.numeric(par2)*100)
par3 <- as.numeric(par3)*100
if(par4=='') par4 <- 0
par4 <- as.numeric(par4)
numlam <- par2 + par3 + 1
x <- x + par4
n <- length(x)
c <- array(NA,dim=c(numlam))
l <- array(NA,dim=c(numlam))
mx <- -1
mxli <- -999
for (i in 1:numlam)
{
l[i] <- (i-par2-1)/100
if (l[i] != 0)
{
if (par1 == 'Full Box-Cox transform') x1 <- (x^l[i] - 1) / l[i]
if (par1 == 'Simple Box-Cox transform') x1 <- x^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]
x1.best <- x1
}
}
c
mx
mxli
x1.best
if (mxli != 0)
{
if (par1 == 'Full Box-Cox transform') x1 <- (x^mxli - 1) / mxli
if (par1 == 'Simple Box-Cox transform') x1 <- x^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)
if(mx<0) {
a<-table.row.start(a)
a<-table.element(a,'Warning: maximum correlation is negative! The Box-Cox transformation must not be used.',2)
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
if(par5=='Yes') {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Obs.',header=T)
a<-table.element(a,'Original',header=T)
a<-table.element(a,'Transformed',header=T)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i)
a<-table.element(a,x[i])
a<-table.element(a,x1.best[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
}