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Description of Statistical Computation

Author's title

Box-Cox Linearity Plot: Totale consumptiegoederen vs niet-duurzame consumpt...

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 08:34:22 -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/t1228923435av1gb1whtu81xdg.htm/, Retrieved Fri, 17 May 2024 06:17:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32003, Retrieved Fri, 17 May 2024 06:17:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170

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-Cox Linearity...] [2008-12-10 15:34:22] [6aa66640011d9b98524a5838bcf7301d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
99,5
98,2
108,9
100,0
105,0
108,4
96,7
100,5
115,6
114,9
110,7
107,7
113,5
106,9
119,6
109,4
106,9
118,7
108,9
113,1
125,1
126,5
122,7
127,5
107,1
112,0
122,1
111,5
113,2
128,2
115,1
117,4
132,0
130,8
128,0
132,7
117,0
110,9
123,5
117,4
122,7
123,5
111,5
113,8
131,2
127,0
126,2
121,2
118,8
117,9
135,2
120,7
126,4
129,6
113,4
120,5
135,5
137,6
130,6
133,1
121,5
120,5
136,9
123,7
128,5
135,0
120,9
121,1
132,2
134,5
133,6
136,1
124,5
124,6
133,5
132,3
125,3
135,5
121,2
117,5
135,9

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32003&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]3 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=32003&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32003&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 time3 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Box-Cox Linearity Plot
# observations x81
maximum correlation0.940537174669346
optimal lambda(x)-1.48
Residual SD (orginial)3.68937452824637
Residual SD (transformed)3.54210801681399

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 81 \tabularnewline
maximum correlation & 0.940537174669346 \tabularnewline
optimal lambda(x) & -1.48 \tabularnewline
Residual SD (orginial) & 3.68937452824637 \tabularnewline
Residual SD (transformed) & 3.54210801681399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32003&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]0.940537174669346[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-1.48[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]3.68937452824637[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]3.54210801681399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32003&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32003&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 x81
maximum correlation0.940537174669346
optimal lambda(x)-1.48
Residual SD (orginial)3.68937452824637
Residual SD (transformed)3.54210801681399


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')