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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 13:55:32 -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/t1261256639goxwoo4db7sl4ho.htm/, Retrieved Sat, 04 May 2024 01:52:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=69751, Retrieved Sat, 04 May 2024 01:52:41 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsShw Paper waarde ideale lambda??? via box cox linearity
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-   PD  [Bivariate Data Series] [WS4 part 1 scatte...] [2009-10-30 13:19:29] [c620fe7250af73a91c51407172a85dab]
- RMP     [Bivariate Explorative Data Analysis] [WS4 part 1] [2009-10-30 13:27:38] [c620fe7250af73a91c51407172a85dab]
- RMPD        [Box-Cox Linearity Plot] [Paper waarde idea...] [2009-12-19 20:55:32] [51108381f3361ca8af49c4f74052c840] [Current]
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Dataseries X:
103,1
103,1
103,3
103,5
103,3
103,5
103,8
103,9
103,9
104,2
104,6
104,9
105,2
105,2
105,6
105,6
106,2
106,3
106,4
106,9
107,2
107,3
107,3
107,4
107,55
107,87
108,37
108,38
107,92
108,03
108,14
108,3
108,64
108,66
109,04
109,03
109,03
109,54
109,75
109,83
109,65
109,82
109,95
110,12
110,15
110,2
109,99
110,14
110,14
110,81
110,97
110,99
109,73
109,81
110,02
110,18
110,21
110,25
110,36
110,51
110,64
110,95
111,18
111,19
111,69
111,7
111,83
111,77
111,73
112,01
111,86
112,04
Dataseries Y:
152,60
153,32
165,50
139,18
136,53
115,92
96,65
83,77
84,66
106,03
86,92
54,66
151,66
121,27
132,95
119,64
122,16
117,44
106,69
87,45
80,98
110,30
87,01
55,73
146,00
137,54
138,54
135,62
107,27
99,04
91,36
68,35
82,59
98,41
71,25
47,58
130,83
113,60
125,69
113,60
97,12
104,43
91,84
75,11
89,24
110,23
78,42
68,45
122,81
129,66
159,06
139,03
102,16
113,59
81,46
77,36
87,57
101,23
87,21
64,94
133,12
117,99
135,90
125,67
108,03
128,31
84,74
86,38
92,24
95,83
92,33
54,27




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69751&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69751&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69751&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'Gwilym Jenkins' @ 72.249.127.135







Box-Cox Linearity Plot
# observations x72
maximum correlation0.250495505312927
optimal lambda(x)-2
Residual SD (orginial)26.5363802990022
Residual SD (transformed)26.4947006281367

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 72 \tabularnewline
maximum correlation & 0.250495505312927 \tabularnewline
optimal lambda(x) & -2 \tabularnewline
Residual SD (orginial) & 26.5363802990022 \tabularnewline
Residual SD (transformed) & 26.4947006281367 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=69751&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]72[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.250495505312927[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]26.5363802990022[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]26.4947006281367[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=69751&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=69751&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 x72
maximum correlation0.250495505312927
optimal lambda(x)-2
Residual SD (orginial)26.5363802990022
Residual SD (transformed)26.4947006281367



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')