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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 computationSat, 07 Nov 2009 08:41:43 -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/07/t1257608768msiq7c9n2c5qi1o.htm/, Retrieved Mon, 06 May 2024 23:10:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54437, Retrieved Mon, 06 May 2024 23:10:03 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact235
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]
-    D    [Box-Cox Linearity Plot] [WS 6: Box-Cox Lin...] [2009-11-07 15:41:43] [b9056af0304697100f456398102f1287] [Current]
- RM D      [Bagplot] [WS 6: Bag Plot] [2009-11-07 15:52:54] [8cf9233b7464ea02e32be3b30fdac052]
-   P         [Bagplot] [WS 6: Bag Plot] [2009-11-12 17:07:28] [b97b96148b0223bc16666763988dc147]
-   PD        [Bagplot] [Paper: Bivariate ...] [2009-12-17 23:06:13] [8cf9233b7464ea02e32be3b30fdac052]
- RM D      [Bivariate Kernel Density Estimation] [WS 6: Bivariate K...] [2009-11-07 15:57:00] [8cf9233b7464ea02e32be3b30fdac052]
-   P         [Bivariate Kernel Density Estimation] [WS 6: Bivariate K...] [2009-11-12 17:09:08] [b97b96148b0223bc16666763988dc147]
- RM D      [Kendall tau Rank Correlation] [WS 6: Bivariate K...] [2009-11-07 15:59:39] [8cf9233b7464ea02e32be3b30fdac052]
-             [Kendall tau Rank Correlation] [WS 6: Bivariate K...] [2009-11-12 17:11:19] [b97b96148b0223bc16666763988dc147]
-    D      [Box-Cox Linearity Plot] [WS 6: Box-Cox Lin...] [2009-11-12 17:05:09] [b97b96148b0223bc16666763988dc147]
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Dataseries X:
7,2
7,4
8,8
9,3
9,3
8,7
8,2
8,3
8,5
8,6
8,5
8,2
8,1
7,9
8,6
8,7
8,7
8,5
8,4
8,5
8,7
8,7
8,6
8,5
8,3
8
8,2
8,1
8,1
8
7,9
7,9
8
8
7,9
8
7,7
7,2
7,5
7,3
7
7
7
7,2
7,3
7,1
6,8
6,4
6,1
6,5
7,7
7,9
7,5
6,9
6,6
6,9
7,7
8
8
7,7
Dataseries Y:
17
18
23,8
25,5
25,6
23,7
22
21,3
20,7
20,4
20,3
20,4
19,8
19,5
23,1
23,5
23,5
22,9
21,9
21,5
20,5
20,2
19,4
19,2
18,8
18,8
22,6
23,3
23
21,4
19,9
18,8
18,6
18,4
18,6
19,9
19,2
18,4
21,1
20,5
19,1
18,1
17
17,1
17,4
16,8
15,3
14,3
13,4
15,3
22,1
23,7
22,2
19,5
16,6
17,3
19,8
21,2
21,5
20,6




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54437&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54437&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54437&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Box-Cox Linearity Plot
# observations x60
maximum correlation0.810429105734527
optimal lambda(x)-0.95
Residual SD (orginial)1.55417448188693
Residual SD (transformed)1.54130056330464

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.810429105734527 \tabularnewline
optimal lambda(x) & -0.95 \tabularnewline
Residual SD (orginial) & 1.55417448188693 \tabularnewline
Residual SD (transformed) & 1.54130056330464 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54437&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]0.810429105734527[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-0.95[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]1.55417448188693[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]1.54130056330464[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54437&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54437&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 correlation0.810429105734527
optimal lambda(x)-0.95
Residual SD (orginial)1.55417448188693
Residual SD (transformed)1.54130056330464



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')