FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 07:28:51 -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/t1226328212ad097flbo25gso4.htm/, Retrieved Sun, 19 May 2024 11:28:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23090, Retrieved Sun, 19 May 2024 11:28:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

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 14:28:51] [63302faa1e3976bf98d1de42298c0b24] [Current]
Feedback Forum
2008-11-19 14:45:57 [Mehmet Yilmaz] [reply] 
Met de Box-Cox Linearity Plot kunnen we een tijdreeks transformeren en op die manier interpretatie fouten voorkomen. vb. De scatterplot doet denken dat er een lineair verband bestaat, maar eigenlijk is er geen verband.
Hier worden de correlaties berekend tussen de verschillende waarden en de hoogste hiervan wordt genomen.

Als resultaat bekomen we een maximum correlatie van 0.946555596558827 bij een optimale lambda van -2. De residual standard deviation bedraagt 0.805845438367848 en de getransformeerde 0.799821196706899. Dit zijn hoge waarden die in dicht bij elkaar liggen. Dus kunnen we ervan uitgaan dat er een hoge associatiegraad bestaat.

De andere 2 grafieken geven eveneens de correlatie weer. Dankzij de afstand van de puntjes kunnen we de waarde van de correlatie zien. Hoe dichter bij de lijn hoe hoger de correlatie.
2008-11-23 14:46:28 [Chi-Kwong Man] [reply] 
Box-Cox transformatie: Met een bepaald formule kan men heel gemakkelijk een probleem oplossen. De computer berekend alle lambda waardes tussen -2 en +2, diegene met de hoogste correlatie wordt toegepast, maar als je maximum niet kan zien kan je geen besluit vormen.
  2008-11-23 20:41:20 [Elias Van Deun] [reply] 
Om even in te pikken op het antwoord van de vorige student. Bij een rechte kan je het maximum niet besluiten, bij een kromme wel.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
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

Tables (Output of Computation)





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=23090&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=23090&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23090&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Box-Cox Linearity Plot
# observations x60
maximum correlation0.946555596558827
optimal lambda(x)-2
Residual SD (orginial)0.805845438367848
Residual SD (transformed)0.799821196706899

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.946555596558827 \tabularnewline
optimal lambda(x) & -2 \tabularnewline
Residual SD (orginial) & 0.805845438367848 \tabularnewline
Residual SD (transformed) & 0.799821196706899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23090&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]0.946555596558827[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]0.805845438367848[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]0.799821196706899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23090&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23090&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 correlation0.946555596558827
optimal lambda(x)-2
Residual SD (orginial)0.805845438367848
Residual SD (transformed)0.799821196706899


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')