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Author*The author of this computation has been verified*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationWed, 10 Dec 2008 10:39:37 -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/Dec/10/t12289308567dt4f2r05ejzxcc.htm/, Retrieved Sun, 19 May 2024 04:12:31 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32045, Retrieved Sun, 19 May 2024 04:12:31 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact182
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Box-Cox Linearity Plot] [Paper: Box-Cox Li...] [2008-12-10 15:08:45] [b518240a1c80d4f939bf8b3e34f77cec]
-         [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-12-10 17:39:37] [6aa66640011d9b98524a5838bcf7301d] [Current]
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Dataseries X:
97,7
101,5
119,6
108,1
117,8
125,5
89,2
92,3
104,6
122,8
96,0
94,6
93,3
101,1
114,2
104,7
113,3
118,2
83,6
73,9
99,5
97,7
103,0
106,3
92,2
101,8
122,8
111,8
106,3
121,5
81,9
85,4
110,9
117,3
106,3
105,5
101,3
105,9
126,3
111,9
108,9
127,2
94,2
85,7
116,2
107,2
110,6
112,0
104,5
112,0
132,8
110,8
128,7
136,8
94,9
88,8
123,2
125,3
122,7
125,7
116,3
118,7
142,0
127,9
131,9
152,3
110,8
99,1
135,0
133,2
131,0
133,9
119,9
136,9
148,9
145,1
142,4
159,6
120,7
109,0
142,0
Dataseries Y:
98,5
97,0
103,3
99,6
100,1
102,9
95,9
94,5
107,4
116,0
102,8
99,8
109,6
103,0
111,6
106,3
97,9
108,8
103,9
101,2
122,9
123,9
111,7
120,9
99,6
103,3
119,4
106,5
101,9
124,6
106,5
107,8
127,4
120,1
118,5
127,7
107,7
104,5
118,8
110,3
109,6
119,1
96,5
106,7
126,3
116,2
118,8
115,2
110,0
111,4
129,6
108,1
117,8
122,9
100,6
111,8
127,0
128,6
124,8
118,5
114,7
112,6
128,7
111,0
115,8
126,0
111,1
113,2
120,1
130,6
124,0
119,4
116,7
116,5
119,6
126,5
111,3
123,5
114,2
103,7
129,5




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32045&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32045&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32045&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Box-Cox Linearity Plot
# observations x81
maximum correlation0.636089108622783
optimal lambda(x)0.83
Residual SD (orginial)7.55218515108924
Residual SD (transformed)7.55125715659336

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 81 \tabularnewline
maximum correlation & 0.636089108622783 \tabularnewline
optimal lambda(x) & 0.83 \tabularnewline
Residual SD (orginial) & 7.55218515108924 \tabularnewline
Residual SD (transformed) & 7.55125715659336 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32045&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]81[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.636089108622783[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]0.83[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]7.55218515108924[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]7.55125715659336[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32045&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32045&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 x81
maximum correlation0.636089108622783
optimal lambda(x)0.83
Residual SD (orginial)7.55218515108924
Residual SD (transformed)7.55125715659336



Parameters (Session):
Parameters (R input):
par1 = ; par2 = ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')