Free Statistics

of Irreproducible Research!

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 computationMon, 16 Nov 2009 11:41:42 -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/2009/Nov/16/t1258397076g8qc1138wjl8rrq.htm/, Retrieved Thu, 28 Mar 2024 12:51:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57351, Retrieved Thu, 28 Mar 2024 12:51:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Box-Cox Linearity Plot] [3/11/2009] [2009-11-02 21:47:57] [b98453cac15ba1066b407e146608df68]
- R  D    [Box-Cox Linearity Plot] [] [2009-11-16 18:41:42] [21edaefb91319406e70b6c03c71b58b3] [Current]
Feedback Forum

Post a new message
Dataseries X:
2.6
2.3
2.3
2.6
3.1
2.8
2.5
2.9
3.1
3.1
3.2
2.5
2.6
2.9
2.6
2.4
1.7
2.0
2.2
1.9
1.6
1.6
1.2
1.2
1.5
1.6
1.7
1.8
1.8
1.8
1.3
1.3
1.4
1.1
1.5
2.2
2.9
3.1
3.5
3.6
4.4
4.2
5.2
5.8
5.9
5.4
5.5
4.7
3.1
2.6
2.3
1.9
0.6
0.6
Dataseries Y:
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.00
2.21
2.25
2.25
2.45
2.50
2.50
2.64
2.75
2.93
3.00
3.17
3.25
3.39
3.50
3.50
3.65
3.75
3.75
3.90
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.00
4.18
4.25
4.25
3.97
3.42
2.75
2.31
2.00
1.66
1.31




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=57351&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=57351&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57351&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'Gwilym Jenkins' @ 72.249.127.135







Box-Cox Linearity Plot
# observations x54
maximum correlation0.431124714210493
optimal lambda(x)2
Residual SD (orginial)0.833989570375266
Residual SD (transformed)0.809588846234695

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 54 \tabularnewline
maximum correlation & 0.431124714210493 \tabularnewline
optimal lambda(x) & 2 \tabularnewline
Residual SD (orginial) & 0.833989570375266 \tabularnewline
Residual SD (transformed) & 0.809588846234695 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57351&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]54[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.431124714210493[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]0.833989570375266[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]0.809588846234695[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57351&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57351&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 x54
maximum correlation0.431124714210493
optimal lambda(x)2
Residual SD (orginial)0.833989570375266
Residual SD (transformed)0.809588846234695



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')