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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, 22 Dec 2008 07:11:54 -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/22/t12299552759i35a3bj6ld1w3j.htm/, Retrieved Mon, 13 May 2024 01:14:48 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36077, Retrieved Mon, 13 May 2024 01:14:48 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- R PD  [Univariate Data Series] [Tijdreeks 2 Buite...] [2008-12-11 16:25:30] [2d4aec5ed1856c4828162be37be304d9]
- RMP     [Central Tendency] [Central tendency ...] [2008-12-11 17:41:16] [2d4aec5ed1856c4828162be37be304d9]
- RM D        [Box-Cox Linearity Plot] [Box-Cox linearity...] [2008-12-22 14:11:54] [d7f41258beeebb8716e3f5d39f3cdc01] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16283,6
16726,5
14968,9
14861
14583,3
15305,8
17903,9
16379,4
15420,3
17870,5
15912,8
13866,5
17823,2
17872
17420,4
16704,4
15991,2
16583,6
19123,5
17838,7
17209,4
18586,5
16258,1
15141,6
19202,1
17746,5
19090,1
18040,3
17515,5
17751,8
21072,4
17170
19439,5
19795,4
17574,9
16165,4
19464,6
19932,1
19961,2
17343,4
18924,2
18574,1
21350,6
18594,6
19823,1
20844,4
19640,2
17735,4
19813,6
22160
20664,3
17877,4
21211,2
21423,1
21688,7
23243,2
21490,2
22925,8
23184,8
18562,2
Dataseries Y:
Download CSV
Histogram 
2220,6
2161,5
1863,6
1955,1
1907,4
1889,4
2246,3
2213
1965
2285,6
1983,8
1872,4
2371,4
2287
2198,2
2330,4
2014,4
2066,1
2355,8
2232,5
2091,7
2376,5
1931,9
2025,7
2404,9
2316,1
2368,1
2282,5
2158,6
2174,8
2594,1
2281,4
2547,9
2606,3
2190,8
2262,3
2423,8
2520,4
2482,9
2215,9
2441,9
2333,8
2670,2
2431
2559,3
2661,4
2404,6
2378,3
2489,2
2941
2700,9
2335,6
2770
2764,2
2784,9
2898,8
2853,4
3022,6
2851,4
2630,8

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36077&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36077&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36077&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'George Udny Yule' @ 72.249.76.132






Box-Cox Linearity Plot
# observations x60
maximum correlation0.957207921338445
optimal lambda(x)1.31
Residual SD (orginial)84.0669694419434
Residual SD (transformed)83.8311740062895

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.957207921338445 \tabularnewline
optimal lambda(x) & 1.31 \tabularnewline
Residual SD (orginial) & 84.0669694419434 \tabularnewline
Residual SD (transformed) & 83.8311740062895 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36077&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]0.957207921338445[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]1.31[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]84.0669694419434[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]83.8311740062895[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36077&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36077&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 correlation0.957207921338445
optimal lambda(x)1.31
Residual SD (orginial)84.0669694419434
Residual SD (transformed)83.8311740062895


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')