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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 computationThu, 12 Nov 2009 07:27:45 -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/12/t1258036458ghp8juli1dg7xt1.htm/, Retrieved Fri, 03 May 2024 16:42:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56041, Retrieved Fri, 03 May 2024 16:42:34 +0000
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Original text written by user:Hieruit valt af te leiden dat er een goeie correlatie bestaat tussen deze twee tijdreeksen van Lambda -2 tot 0,5, daarna is er een buiging in neerwaartse zin waar te nemen.
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact137
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Box-Cox Linearity Plot] [Box-Cox linearity...] [2009-11-12 14:27:45] [bef26de542bed2eafc60fe4615b06e47] [Current]
-   PD    [Box-Cox Linearity Plot] [] [2010-12-21 21:16:14] [f47feae0308dca73181bb669fbad1c56]
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Dataseries X:
121.6
118.8
114.0
111.5
97.2
102.5
113.4
109.8
104.9
126.1
80.0
96.8
117.2
112.3
117.3
111.1
102.2
104.3
122.9
107.6
121.3
131.5
89.0
104.4
128.9
135.9
133.3
121.3
120.5
120.4
137.9
126.1
133.2
151.1
105.0
119.0
140.4
156.6
137.1
122.7
125.8
139.3
134.9
149.2
132.3
149.0
117.2
119.6
152.0
149.4
127.3
114.1
102.1
107.7
104.4
102.1
96.0
109.3
90.0
83.9
Dataseries Y:
116.2
111.2
105.8
122.7
99.5
107.9
124.6
115.0
110.3
132.7
99.7
96.5
118.7
112.9
130.5
137.9
115.0
116.8
140.9
120.7
134.2
147.3
112.4
107.1
128.4
137.7
135.0
151.0
137.4
132.4
161.3
139.8
146.0
166.5
143.3
121.0
152.6
154.4
154.6
158.0
142.6
153.4
163.4
167.3
154.8
165.7
144.7
120.9
152.8
160.2
128.3
150.5
117.0
116.0
133.3
116.4
104.0
126.6
92.9
83.6




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=56041&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=56041&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56041&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 correlation0.85357394301735
optimal lambda(x)0.54
Residual SD (orginial)10.8663899226089
Residual SD (transformed)10.8365813073664

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.85357394301735 \tabularnewline
optimal lambda(x) & 0.54 \tabularnewline
Residual SD (orginial) & 10.8663899226089 \tabularnewline
Residual SD (transformed) & 10.8365813073664 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56041&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]0.85357394301735[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]0.54[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]10.8663899226089[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]10.8365813073664[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56041&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56041&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 correlation0.85357394301735
optimal lambda(x)0.54
Residual SD (orginial)10.8663899226089
Residual SD (transformed)10.8365813073664



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')