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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 computationMon, 10 Nov 2008 07:53:44 -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/2008/Nov/10/t12263291566z81hdfryfrurlq.htm/, Retrieved Sun, 19 May 2024 09:26:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23094, Retrieved Sun, 19 May 2024 09:26:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Box-Cox Linearity Plot] [] [2008-11-10 14:53:44] [63302faa1e3976bf98d1de42298c0b24] [Current]
Feedback Forum
2008-11-19 14:57:08 [Mehmet Yilmaz] [reply] 
De student gebruikt hier de Box-Cox Linearity Plot, terwijl hij de Box-Cox Normality Plot zou moeten gebruiken.

Hier is de juiste berekening:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/19/t12271064668t1ldg84y8fnj1r.htm

De maximum correlatie bedraagt 0.957636507341855 bij een optimale lambda van 2.
2008-11-23 14:47:18 [Chi-Kwong Man] [reply] 
Verkeerde methode gebruikt, hier moest men Box-Cox Normality Plot toepassen.
2008-11-23 20:43:45 [Elias Van Deun] [reply] 
Zoals door de vorige student al heeft aangegeven werd hier de Box-Cox Linearity Plot gebruikt in plaats van Box-Cox Normality Plot.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
107,06
109,98
112,64
112,89
112,9
112,9
112,91
112,99
113,01
113
113,07
113,07
113,21
114,13
114,59
114,88
115,3
115,33
115,36
115,41
115,43
115,43
115,43
115,43
115,56
115,88
116,02
116,09
116,28
116,28
116,28
116,25
116,07
116,08
116,07
115,92
116,07
117,22
117,75
117,78
117,78
117,81
117,81
117,74
117,75
117,76
117,76
117,75
117,8
118,09
118,95
119,03
118,9
118,9
118,9
118,87
118,88
119,36
119,39
119,47
Dataseries Y:
Download CSV
Histogram 
105,15
105,24
105,57
105,62
106,17
106,27
106,41
106,94
107,16
107,32
107,32
107,35
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
110,21
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
110,6
110,95
111,18
111,19
111,69
111,7
111,83
111,77
111,73
112,01
111,86
112,04

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=23094&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=23094&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23094&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 x60
maximum correlation0.947814285417643
optimal lambda(x)2
Residual SD (orginial)0.607614707024691
Residual SD (transformed)0.59612111149271

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.947814285417643 \tabularnewline
optimal lambda(x) & 2 \tabularnewline
Residual SD (orginial) & 0.607614707024691 \tabularnewline
Residual SD (transformed) & 0.59612111149271 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23094&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]0.947814285417643[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]0.607614707024691[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]0.59612111149271[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23094&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23094&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 correlation0.947814285417643
optimal lambda(x)2
Residual SD (orginial)0.607614707024691
Residual SD (transformed)0.59612111149271


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')