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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationTue, 11 Nov 2008 07:14:49 -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/t1226413005u56hufpnoe28h4c.htm/, Retrieved Sun, 19 May 2024 09:38:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23502, Retrieved Sun, 19 May 2024 09:38:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact118
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Box-Cox Linearity Plot] [Various EDA Topic...] [2008-11-11 14:14:49] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
Feedback Forum
2008-11-12 16:12:50 [Veerle Jackers] [reply
Ik heb niet vermeld in mijn oplossing welke de optimale lambda is. Het is hier toch vrij duidelijk dat er een maximum bereikt wordt. Wanneer lambda 1,34 is, is er een maximale correlatie.
2008-11-24 18:35:28 [Niels Herremans] [reply
Op de Box Cox Linearity plot moet er nagegaan worden waar de lambda een maximum bereikt. Daar is er de beste correlatie. En dat is hier inderdaad bij 1.34

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Dataseries X:
0,33
0,33
0,32
0,33
0,34
0,36
0,34
0,33
0,35
0,31
0,28
0,26
0,26
0,26
0,29
0,30
0,30
0,28
0,29
0,29
0,32
0,33
0,29
0,31
0,33
0,36
0,39
0,30
0,27
0,28
0,29
0,30
0,30
0,30
0,31
0,30
0,31
0,29
0,32
0,33
0,35
0,35
0,36
0,40
0,40
0,47
0,43
0,38
0,38
0,40
0,45
0,47
0,45
0,50
0,54
0,55
0,59
0,51
0,50
0,50
Dataseries Y:
1,00
1,04
1,02
1,07
1,12
1,08
1,02
1,01
1,04
0,98
0,95
0,94
0,94
0,96
0,97
1,03
1,01
0,99
1,00
1,00
1,02
1,01
0,99
0,98
1,01
1,03
1,03
1,00
0,96
0,97
0,98
1,02
1,04
1,01
1,01
1,00
1,01
1,02
1,03
1,06
1,12
1,12
1,13
1,13
1,13
1,17
1,14
1,08
1,07
1,12
1,14
1,21
1,20
1,23
1,29
1,31
1,37
1,35
1,26
1,26




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23502&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23502&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23502&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132







Box-Cox Linearity Plot
# observations x60
maximum correlation0.959183895229564
optimal lambda(x)1.34
Residual SD (orginial)0.0299020773169203
Residual SD (transformed)0.0296903566007326

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.959183895229564 \tabularnewline
optimal lambda(x) & 1.34 \tabularnewline
Residual SD (orginial) & 0.0299020773169203 \tabularnewline
Residual SD (transformed) & 0.0296903566007326 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23502&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]60[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.959183895229564[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]1.34[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]0.0299020773169203[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]0.0296903566007326[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23502&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23502&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 Linearity Plot
# observations x60
maximum correlation0.959183895229564
optimal lambda(x)1.34
Residual SD (orginial)0.0299020773169203
Residual SD (transformed)0.0296903566007326



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(x1,y)
if (mx < abs(c[i]))
{
mx <- abs(c[i])
mxli <- l[i]
}
}
c
mx
mxli
if (mxli != 0)
{
x1 <- (x^mxli - 1) / mxli
} else {
x1 <- log(x)
}
r<-lm(y~x)
se <- sqrt(var(r$residuals))
r1 <- lm(y~x1)
se1 <- sqrt(var(r1$residuals))
bitmap(file='test1.png')
plot(l,c,main='Box-Cox Linearity Plot',xlab='Lambda',ylab='correlation')
grid()
dev.off()
bitmap(file='test2.png')
plot(x,y,main='Linear Fit of Original Data',xlab='x',ylab='y')
abline(r)
grid()
mtext(paste('Residual Standard Deviation = ',se))
dev.off()
bitmap(file='test3.png')
plot(x1,y,main='Linear Fit of Transformed Data',xlab='x',ylab='y')
abline(r1)
grid()
mtext(paste('Residual Standard Deviation = ',se1))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Box-Cox Linearity 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(x)',header=TRUE)
a<-table.element(a,mxli)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Residual SD (orginial)',header=TRUE)
a<-table.element(a,se)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Residual SD (transformed)',header=TRUE)
a<-table.element(a,se1)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')