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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 computationWed, 10 Dec 2008 08:02:30 -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/10/t1228921490zedwrmbe39lu2ay.htm/, Retrieved Fri, 17 May 2024 12:54:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31990, Retrieved Fri, 17 May 2024 12:54:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact172

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] [Paper G6 box cox ...] [2007-11-10 14:35:12] [70ea62757742573c580c86c5f8652367]
-    D    [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-12-10 15:02:30] [732c025e7dfb439ac3d0c7b7e70fa7a1] [Current]
-    D      [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-12-18 13:19:27] [7506b5e9e41ec66c6657f4234f97306e]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,2
106,9
118,6
111,9
119,0
116,3
116,2
115,6
107,5
116,8
124,1
115,0
105,3
104,1
119,6
112,2
109,6
121,8
108,8
111,5
108,5
115,4
119,3
116,5
101,9
96,6
116,6
112,5
103,7
118,5
105,0
105,0
109,1
112,6
108,2
114,4
95,9
90,8
115,0
99,8
103,0
108,4
99,2
100,6
107,1
107,0
111,9
115,6
97,7
97,3
111,8
99,3
104,6
113,3
98,7
98,2
102,5
100,8
111,4
108,9
90,4
94,6
104,3
99,0
103,0
105,1
98,9
101,0
96,5
102,8
112,3
106,5
91,9
92,7
104,2
101,7
102,8
105,6
96,9
97,6
93,7
102,1
106,6
100,2
92,0
86,8
104,8
100,0
96,8
110,6
100,7
101,5
Dataseries Y:
Download CSV
Histogram 
18 562,2 
23 184,8 
22 925,8 
21 490,2 
23 243,2 
21 688,7 
21 423,1 
21 211,2 
17 877,4  
20 664,3  
22 160,0  
19 813,6  
17 735,4  
19 640,2  
20 844,4  
19 823,1  
18 594,6  
21 350,6  
18 574,1  
18 924,2  
17 343,4  
19 961,2  
19 932,1  
19 464,6  
16 165,4  
17 574,9  
19 795,4  
19 439,5  
17 170,0  
21 072,4  
17 751,8  
17 515,5  
18 040,3  
19 090,1  
17 746,5  
19 202,1  
15 141,6  
16 258,1  
18 586,5  
17 209,4  
17 838,7  
19 123,5  
16 583,6  
15 991,2  
16 704,4  
17 420,4  
17 872,0  
17 823,2  
13 866,5  
15 912,8  
17 870,5  
15 420,3  
16 379,4  
17 903,9  
15 305,8  
14 583,3  
14 861,0  
14 968,9  
16 726,5  
16 283,6  
11 703,7  
15 101,8  
15 469,7  
14 956,9  
15 370,6  
15 998,1  
14 725,1  
14 768,9  
13 659,6  
15 070,3  
16 943,0  
15 761,3  
12 083,0  
15 023,6  
15 106,5  
15 498,6  
15 258,9  
15 859,4  
14 205,3  
14 291,1  
12 875,1  
14 755,3  
15 873,2  
14 803,0  
12 520,2  
14 568,3  
15 644,8  
15 454,9  
14 254,0  
16 754,8  
14 944,2  
15 044,5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31990&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31990&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31990&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Box-Cox Linearity Plot
# observations x92
maximum correlation0.850772722201499
optimal lambda(x)2
Residual SD (orginial)1375.16206970234
Residual SD (transformed)1359.91456514045

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 92 \tabularnewline
maximum correlation & 0.850772722201499 \tabularnewline
optimal lambda(x) & 2 \tabularnewline
Residual SD (orginial) & 1375.16206970234 \tabularnewline
Residual SD (transformed) & 1359.91456514045 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31990&T=1

[TABLE]
[ROW][C]Box-Cox Linearity Plot[/C][/ROW]
[ROW][C]# observations x[/C][C]92[/C][/ROW]
[ROW][C]maximum correlation[/C][C]0.850772722201499[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]2[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]1375.16206970234[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]1359.91456514045[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31990&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31990&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 x92
maximum correlation0.850772722201499
optimal lambda(x)2
Residual SD (orginial)1375.16206970234
Residual SD (transformed)1359.91456514045


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')