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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, 19 Dec 2009 06:09:27 -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/Dec/19/t1261228294chlzitds919kzoe.htm/, Retrieved Sat, 04 May 2024 00:13:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69567, Retrieved Sat, 04 May 2024 00:13:59 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
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...] [2009-12-19 13:09:27] [e458b4e05bf28a297f8af8d9f96e59d6] [Current]
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Dataseries X:
100,0
100,6
114,2
91,5
94,7
110,6
71,3
104,1
112,3
110,2
112,9
95,1
103,1
101,9
100,4
106,9
100,7
114,3
73,3
105,9
113,9
112,1
117,5
97,5
112,3
106,9
120,9
92,7
110,9
116,5
77,1
113,1
115,9
123,5
123,6
101,5
121,0
112,2
126,0
101,8
117,9
122,2
82,7
120,5
120,3
134,2
128,2
100,5
126,0
122,9
106,1
130,4
121,3
126,1
88,7
118,7
129,3
136,2
123,0
103,5
Dataseries Y:
100,0
95,3
90,7
88,4
86,0
86,0
95,3
95,3
88,4
86,0
81,4
83,7
95,3
88,4
86,0
83,7
76,7
79,1
86,0
86,0
79,1
76,7
69,8
69,8
76,7
69,8
67,4
65,1
58,1
60,5
65,1
62,8
55,8
51,2
48,8
48,8
53,5
48,8
46,5
44,2
39,5
41,9
48,8
46,5
41,9
39,5
37,2
37,2
41,9
39,5
39,5
34,9
34,9
34,9
41,9
41,9
39,5
39,5
41,9
46,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69567&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69567&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69567&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'Gwilym Jenkins' @ 72.249.127.135







Box-Cox Linearity Plot
# observations x60
maximum correlation0.550756474504925
optimal lambda(x)2
Residual SD (orginial)17.7896418350869
Residual SD (transformed)17.4661036904387

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.550756474504925 \tabularnewline
optimal lambda(x) & 2 \tabularnewline
Residual SD (orginial) & 17.7896418350869 \tabularnewline
Residual SD (transformed) & 17.4661036904387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69567&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]0.550756474504925[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]17.7896418350869[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]17.4661036904387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69567&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69567&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 correlation0.550756474504925
optimal lambda(x)2
Residual SD (orginial)17.7896418350869
Residual SD (transformed)17.4661036904387



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')