Free Statistics

of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationTue, 11 Nov 2008 09:29:34 -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/11/t12264211918e8crb8hkw92uof.htm/, Retrieved Sun, 19 May 2024 11:29:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23691, Retrieved Sun, 19 May 2024 11:29:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact149
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Box-Cox Linearity Plot] [Q3] [2008-11-11 16:29:34] [ee28d11f695cd3bc1f8bbd77ba77987a] [Current]
Feedback Forum
2008-11-19 20:59:07 [Nathalie Koulouris] [reply
De juiste berekeningsmethode werd gebruikt maar met te weinig observaties. De berekening werd ook niet verder gemotiveerd.
2008-11-22 09:51:07 [Astrid Sniekers] [reply
Q3:

Q3:

De student heeft zijn/haar tijdreeksen niet in het document geplaatst. Hierdoor weet ik niet welke datasets hij/zij hier gebruikt. Ook zegt de student dit niet in zijn/haar document. Er zijn geen conclusies getrokken. De student zal aan de hand van de oplossingen die in de les zijn gegeven, de oefening opnieuw moeten maken.

Ook zijn de tijdreeksen die de student gebruikt niet correct. Een tijdreeks moet minstens 60 maandelijkse observaties bevatten. Hij of zij gebruikt veel te weinig observaties.


Q4+Q5:
De student heeft geen poging gedaan om een oplossing te formuleren. De vragen zijn onbeantwoord gebleven.

Post a new message
Dataseries X:
88.6
71.6
93.3
84.3
80.6
75.2
69.7
82
69.4
83.3
79.6
82.6
80.6
83.5
76.3
Dataseries Y:
20
16
19.8
18.4
17.1
15.5
14.7
17.1
15.4
16.2
15
17.2
16
17
14.4




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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23691&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23691&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23691&T=0

As an alternative you can also use a 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







Box-Cox Linearity Plot
# observations x15
maximum correlation0.848376278701644
optimal lambda(x)2
Residual SD (orginial)0.936177904924395
Residual SD (transformed)0.9010511536877

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 15 \tabularnewline
maximum correlation & 0.848376278701644 \tabularnewline
optimal lambda(x) & 2 \tabularnewline
Residual SD (orginial) & 0.936177904924395 \tabularnewline
Residual SD (transformed) & 0.9010511536877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23691&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]15[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.848376278701644[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]0.936177904924395[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]0.9010511536877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23691&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23691&T=1

As an alternative you can also use a QR Code:  

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

Box-Cox Linearity Plot
# observations x15
maximum correlation0.848376278701644
optimal lambda(x)2
Residual SD (orginial)0.936177904924395
Residual SD (transformed)0.9010511536877



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')