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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationSat, 03 Nov 2007 10:10:44 -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/2007/Nov/03/5s2yode1h7x7s071194109772.htm/, Retrieved Sat, 04 May 2024 23:40:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=178, Retrieved Sat, 04 May 2024 23:40:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbox cox linearity plot : voeding - niet-voeding
Estimated Impact121

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Box-Cox Linearity Plot] [opdr 4 q3 ] [2007-11-03 17:10:44] [0c12eff582f43eaf43ae2f09e879befe] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92,58
93,15
93,7
93,34
93,93
94,41
94,3
94,44
96,09
95,99
96,23
95,64
94,88
95,48
95,52
96,18
96,82
96,81
96,25
96,24
96,95
96,25
96,04
95,78
95,86
96,02
96,34
96,84
96,73
96,34
96,6
96,64
97,2
97,5
96,99
97,08
97,55
98,42
98,78
97,49
96,99
97,16
97,29
97,8
98,12
98,03
98,11
98,07
98,21
98,48
98,83
99,2
99,88
99,71
100,03
100,6
100,85
101,96
101,4
100,81
100,66
101,55
102,23
102,9
102,68
103,41
104,62
104,93
105,88
105,18
104,54
104,58
104,34
104,66
104,73
105,44
105,72
105,68
105,9
105,97
105,21
104,75
104,89
105,26
104,84
105,47
105,4
105,73
105,72
105,63
105,97
105,92
106,32
Dataseries Y:
Download CSV
Histogram 
89,28
89,47
89,53
90,72
90,91
91,38
91,49
90,9
90,93
90,57
91,28
90,83
91,5
91,58
92,49
94,16
95,46
95,8
95,32
95,41
95,35
95,68
95,59
94,96
96,92
96,06
96,59
96,67
97,27
96,38
96,47
96,05
96,76
96,51
96,55
95,97
97
97,46
97,9
98,42
98,54
99
98,94
99,02
100,07
98,72
98,73
98,04
99,08
99,22
99,57
100,44
100,84
100,75
100,49
99,98
99,96
99,76
100,11
99,79
100,29
101,12
102,65
102,71
103,39
102,8
102,07
102,15
101,21
101,27
101,86
101,65
101,94
102,62
102,71
103,39
104,51
104,09
104,29
104,57
105,39
105,15
106,13
105,46
106,47
106,62
106,52
108,04
107,15
107,32
107,76
107,26
107,89

Tables (Output of Computation)





Summary of compuational 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 compuational 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=178&T=0

[TABLE]
[ROW][C]Summary of compuational 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=178&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=178&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of compuational 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 x93
maximum correlation0.937233047151626
optimal lambda(x)-2
Residual SD (orginial)1.82092679782354
Residual SD (transformed)1.74181018188433

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 93 \tabularnewline
maximum correlation & 0.937233047151626 \tabularnewline
optimal lambda(x) & -2 \tabularnewline
Residual SD (orginial) & 1.82092679782354 \tabularnewline
Residual SD (transformed) & 1.74181018188433 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=178&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]93[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.937233047151626[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]1.82092679782354[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]1.74181018188433[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=178&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=178&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Box-Cox Linearity Plot
# observations x93
maximum correlation0.937233047151626
optimal lambda(x)-2
Residual SD (orginial)1.82092679782354
Residual SD (transformed)1.74181018188433


Figures (Output of Computation)

Input Parameters & R Code

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')