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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_boxcoxlin.wasp
Title produced by softwareBox-Cox Linearity Plot
Date of computationSun, 04 Nov 2007 14:16:51 -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/2007/Nov/04/8jml2ltc746n5yf1194210909.htm/, Retrieved Sun, 05 May 2024 18:18:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=288, Retrieved Sun, 05 May 2024 18:18:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact248

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2007-11-04 21:16:51] [6bdd947de0ee04552c8f0fc807f31807] [Current]
- RM D    [Box-Cox Normality Plot] [Box-Cox norm. Fra...] [2007-11-05 20:01:46] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9884,9
10174,5
11395,4
10760,2
10570,1
10536
9902,6
8889
10837,3
11624,1
10509
10984,9
10649,1
10855,7
11677,4
10760,2
10046,2
10772,8
9987,7
8638,7
11063,7
11855,7
10684,5
11337,4
10478
11123,9
12909,3
11339,9
10462,2
12733,5
10519,2
10414,9
12476,8
12384,6
12266,7
12919,9
11497,3
12142
13919,4
12656,8
12034,1
13199,7
10881,3
11301,2
13643,9
12517
13981,1
14275,7
13435
13565,7
16216,3
12970
14079,9
14235
12213,4
12581
14130,4
14210,8
14378,5
13142,8
13714,7
13621,9
15379,8
14441,8
15354,8
15537,8
14552,7
Dataseries Y:
Download CSV
Histogram 
1962,3
2095,2
2161
2115,1
1929
2004,5
2009,9
1524,9
2061,1
2261,6
2103,6
2224,3
2173,8
2119,2
2226,4
2159,6
1918,3
2116,1
1948,3
1514,3
2180,5
2312,6
2019,8
2200,8
2028,9
2178,7
2433,7
2230,5
1884,2
2372,7
1918,6
1679,4
2327,3
2225,2
2211,7
2463,6
2029,5
2173,6
2387
2234
2179,9
2397
1960,2
1824,1
2479,3
2234,9
2345,9
2428,9
2179,4
2216,9
2642,3
2340,5
2474,6
2641,8
2165,1
1996,2
2562,9
2529,9
2549,6
2455,1
2472
2424,7
2820,1
2666
2654,6
2732,2
2546,9

Tables (Output of Computation)





Summary of compuational 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 compuational 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=288&T=0

[TABLE]
[ROW][C]Summary of compuational 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=288&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=288&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 compuational 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 x67
maximum correlation0.906902469587684
optimal lambda(x)-0.53
Residual SD (orginial)116.027216180039
Residual SD (transformed)113.027607339515

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 67 \tabularnewline
maximum correlation & 0.906902469587684 \tabularnewline
optimal lambda(x) & -0.53 \tabularnewline
Residual SD (orginial) & 116.027216180039 \tabularnewline
Residual SD (transformed) & 113.027607339515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=288&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]67[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.906902469587684[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-0.53[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]116.027216180039[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]113.027607339515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=288&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=288&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 x67
maximum correlation0.906902469587684
optimal lambda(x)-0.53
Residual SD (orginial)116.027216180039
Residual SD (transformed)113.027607339515


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')