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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 computationMon, 09 Nov 2009 07:16:08 -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/09/t1257776270ti8decw0rzf4f52.htm/, Retrieved Fri, 19 Apr 2024 01:39:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54832, Retrieved Fri, 19 Apr 2024 01:39:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact196
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [3/11/2009] [2009-11-02 21:10:41] [b98453cac15ba1066b407e146608df68]
-    D  [Notched Boxplots] [ws 6 1] [2009-11-04 11:54:28] [6e4e01d7eb22a9f33d58ebb35753a195]
- RMPD    [Univariate Explorative Data Analysis] [ws 6 kla] [2009-11-04 11:57:24] [6e4e01d7eb22a9f33d58ebb35753a195]
- RMPD        [Box-Cox Linearity Plot] [WS6_boxcox] [2009-11-09 14:16:08] [7a6d96edf94be87996de99db5f42363b] [Current]
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Dataseries X:
70,5
77,7
56,0
56,8
69,2
71,3
79,4
80,8
72,2
69,8
73,0
82,0
76,3
65,3
51,4
60,5
83,0
89,8
78,6
85,8
69,7
69,4
76,6
76,4
77,1
79,0
67,5
60,0
71,7
79,3
66,0
78,1
57,1
49,6
64,0
57,8
61,6
82,4
61,8
62,1
79,5
65,4
72,5
84,6
62,5
65,1
79,0
65,9
66,1
83,3
40,6
58,6
67,3
68,2
59,5
65,7
53,4
39,5
51,7
42,3
45,9
54,7
41,8
48,6
57,1
76,5
62,7
53,9
53,5
47,5
49,3
59,9
49,9
54,5
54,2
46,7
61,2
51,8
37,4
41,1
30,0
34,8
45,9
45,1
42,6
49,0
29,6
46,0
Dataseries Y:
102,0
104,7
86,0
92,1
106,9
112,6
101,7
92,0
97,4
97,0
105,4
102,7
98,1
104,5
87,4
89,9
109,8
111,7
98,6
96,9
95,1
97,0
112,7
102,9
97,4
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99,0
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102,0
106,0
105,3
118,8
106,1
109,3
117,2
92,5
104,2
112,5
122,4
113,3
100,0
110,7
112,8
109,8
117,3
109,1
115,9
96,0
99,8
116,8
115,7
99,4
94,3
91,0
93,2
103,1
94,1
91,8
102,7
82,6
89,1




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=54832&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=54832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54832&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 x88
maximum correlation0.372146276239238
optimal lambda(x)-2
Residual SD (orginial)8.80548380256154
Residual SD (transformed)8.6282194820192

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 88 \tabularnewline
maximum correlation & 0.372146276239238 \tabularnewline
optimal lambda(x) & -2 \tabularnewline
Residual SD (orginial) & 8.80548380256154 \tabularnewline
Residual SD (transformed) & 8.6282194820192 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54832&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]88[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.372146276239238[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]8.80548380256154[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]8.6282194820192[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54832&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54832&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 x88
maximum correlation0.372146276239238
optimal lambda(x)-2
Residual SD (orginial)8.80548380256154
Residual SD (transformed)8.6282194820192



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')