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 computationTue, 11 Nov 2008 08:33:03 -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/t1226417608yx8zd97xl755ily.htm/, Retrieved Sun, 19 May 2024 12:04:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=23602, Retrieved Sun, 19 May 2024 12:04:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact134

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Bivariate Kernel Density Estimation] [] [2008-11-11 15:01:49] [29747f79f5beb5b2516e1271770ecb47]
F RMPD  [Partial Correlation] [] [2008-11-11 15:17:50] [29747f79f5beb5b2516e1271770ecb47]
F RMPD    [Trivariate Scatterplots] [] [2008-11-11 15:21:20] [29747f79f5beb5b2516e1271770ecb47]
F RMPD        [Box-Cox Linearity Plot] [] [2008-11-11 15:33:03] [c0a347e3519123f7eef62b705326dad9] [Current]
Feedback Forum
2008-11-24 17:55:20 [Jan Cavents] [reply] 
in dit geval is het moeilijk om de beste lambda te kiezen, aangezien de grafiek een dalende trend weergeeft.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97.6
96.9
105.6
102.8
101.7
104.2
92.7
91.9
106.5
112.3
102.8
96.5
101.0
98.9
105.1
103.0
99.0
104.3
94.6
90.4
108.9
111.4
100.8
102.5
98.2
98.7
113.3
104.6
99.3
111.8
97.3
97.7
115.6
111.9
107.0
107.1
100.6
99.2
108.4
103.0
99.8
115.0
90.8
95.9
114.4
108.2
112.6
109.1
105.0
105.0
118.5
103.7
112.5
116.6
96.6
101.9
116.5
119.3
115.4
108.5
111.5
108.8
121.8
109.6
112.2
119.6
104.1
105.3
115.0
124.1
116.8
107.5
115.6
116.2
116.3
119.0
111.9
118.6
106.7
Dataseries Y:
Download CSV
Histogram 
89,6
92,8
107,6
104,6
103,0
106,9
56,3
93,4
109,1
113,8
97,4
72,5
82,7
88,9
105,9
100,8
94,0
105,0
58,5
87,6
113,1
112,5
89,6
74,5
82,7
90,1
109,4
96,0
89,2
109,1
49,1
92,9
107,7
103,5
91,1
79,8
71,9
82,9
90,1
100,7
90,7
108,8
44,1
93,6
107,4
96,5
93,6
76,5
76,7
84,0
103,3
88,5
99,0
105,9
44,7
94,0
107,1
104,8
102,5
77,7
85,2
91,3
106,5
92,4
97,5
107,0
51,1
98,6
102,2
114,3
99,4
72,5
92,3
99,4
85,9
109,4
97,6
104,7
56,5

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'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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23602&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23602&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23602&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






Box-Cox Linearity Plot
# observations x79
maximum correlation0.586632531902646
optimal lambda(x)-2
Residual SD (orginial)13.5201279416342
Residual SD (transformed)13.4551491723663

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 79 \tabularnewline
maximum correlation & 0.586632531902646 \tabularnewline
optimal lambda(x) & -2 \tabularnewline
Residual SD (orginial) & 13.5201279416342 \tabularnewline
Residual SD (transformed) & 13.4551491723663 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=23602&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]79[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.586632531902646[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]13.5201279416342[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]13.4551491723663[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=23602&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=23602&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 x79
maximum correlation0.586632531902646
optimal lambda(x)-2
Residual SD (orginial)13.5201279416342
Residual SD (transformed)13.4551491723663


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')