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Description of Statistical Computation

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, 14 Nov 2009 13:24:57 -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/14/t12582303780ds30yd811gy4u3.htm/, Retrieved Sun, 28 Apr 2024 11:44:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=57250, Retrieved Sun, 28 Apr 2024 11:44:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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] [Box coc linerity ...] [2009-11-14 20:24:57] [99bf2a1e962091d45abf4c2600a412f9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
91.70
74.44
100.00
74.99
76.27
105.90
74.70
71.60
78.82
88.27
76.11
82.06
78.91
84.36
99.41
93.89
109.62
106.51
79.30
94.51
99.20
90.57
85.54
109.18
109.16
96.00
116.23
93.41
102.27
106.25
87.98
90.11
95.45
100.93
78.97
88.10
90.21
80.36
97.45
80.10
78.50
97.20
81.90
87.20
72.55
105.26
80.90
72.95
83.70
91.92
83.98
87.03
78.21
91.31
74.55
72.25
83.90
76.61
78.10
91.20
Dataseries Y:
Download CSV
Histogram 
101.26
101.08
100.00
98.02
96.76
97.84
107.03
110.09
110.45
110.09
107.03
107.21
106.49
106.13
105.23
103.24
102.16
102.52
111.89
113.33
113.15
110.27
107.21
107.57
106.85
106.31
104.50
103.42
103.24
103.24
111.71
112.79
111.71
105.95
101.98
100.36
101.08
98.92
95.86
94.77
92.07
89.91
100.00
101.80
97.66
94.95
91.89
92.61
93.15
91.53
88.83
88.29
84.50
86.13
95.14
96.22
93.33
91.17
90.45
92.97

Tables (Output of Computation)





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
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57250&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]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57250&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57250&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 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
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Box-Cox Linearity Plot
# observations x60
maximum correlation0.219200006368694
optimal lambda(x)0.67
Residual SD (orginial)7.37850983917767
Residual SD (transformed)7.37838967966154

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.219200006368694 \tabularnewline
optimal lambda(x) & 0.67 \tabularnewline
Residual SD (orginial) & 7.37850983917767 \tabularnewline
Residual SD (transformed) & 7.37838967966154 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=57250&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]0.219200006368694[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]0.67[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]7.37850983917767[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]7.37838967966154[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=57250&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=57250&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 x60
maximum correlation0.219200006368694
optimal lambda(x)0.67
Residual SD (orginial)7.37850983917767
Residual SD (transformed)7.37838967966154


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')