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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, 08 Dec 2008 13:57:51 -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/2008/Dec/08/t1228769940geyy2w1aa4mwxuv.htm/, Retrieved Thu, 16 May 2024 13:29:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31014, Retrieved Thu, 16 May 2024 13:29:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact179

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Notched Boxplots] [workshop 3] [2007-10-26 13:31:48] [e9ffc5de6f8a7be62f22b142b5b6b1a8]
F    D  [Notched Boxplots] [Q1 - Notched Boxplot] [2008-11-03 09:57:32] [a7f04e0e73ce3683561193958d653479]
-    D    [Notched Boxplots] [Notched boxplots:...] [2008-12-08 19:48:56] [a7f04e0e73ce3683561193958d653479]
-    D      [Notched Boxplots] [Notched Boxplots:...] [2008-12-08 19:57:25] [a7f04e0e73ce3683561193958d653479]
- RMPD        [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-12-08 20:23:10] [a7f04e0e73ce3683561193958d653479]
-    D          [Bivariate Kernel Density Estimation] [Bivariate Kernel ...] [2008-12-08 20:26:55] [a7f04e0e73ce3683561193958d653479]
- RMPD            [Trivariate Scatterplots] [Trivariate Scatte...] [2008-12-08 20:42:07] [a7f04e0e73ce3683561193958d653479]
- RMPD                [Box-Cox Linearity Plot] [Bow-Cox Linearity...] [2008-12-08 20:57:51] [f1a30f1149cef3ef3ef69d586c6c3c1c] [Current]
-    D                  [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-12-08 21:02:17] [a7f04e0e73ce3683561193958d653479]
-    D                    [Box-Cox Linearity Plot] [Box-Cox Linearity...] [2008-12-16 20:21:18] [a7f04e0e73ce3683561193958d653479]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
49
46
45
49
47
45
48
51
48
49
51
54
52
52
53
51
55
53
51
52
54
58
57
52
50
53
50
50
51
53
49
54
57
58
56
60
55
54
52
55
56
54
53
59
62
63
64
75
77
79
77
82
83
81
78
79
79
73
72
67
Dataseries Y:
Download CSV
Histogram 
41
35
34
36
39
40
30
33
30
32
41
40
41
40
39
34
34
46
45
44
40
39
37
39
35
26
26
33
27
30
26
27
18
19
13
14
41
21
16
17
9
14
14
16
11
10
6
9
5
7
2
0
8
13
11
19
23
23
43
59

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31014&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31014&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31014&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Box-Cox Linearity Plot
# observations x60
maximum correlation0.58178127280028
optimal lambda(x)-0.23
Residual SD (orginial)11.0604711505628
Residual SD (transformed)11.04155646964

\begin{tabular}{lllllllll}
\hline
Box-Cox Linearity Plot \tabularnewline
# observations x & 60 \tabularnewline
maximum correlation & 0.58178127280028 \tabularnewline
optimal lambda(x) & -0.23 \tabularnewline
Residual SD (orginial) & 11.0604711505628 \tabularnewline
Residual SD (transformed) & 11.04155646964 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31014&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]0.58178127280028[/C][/ROW]
[ROW][C]optimal lambda(x)[/C][C]-0.23[/C][/ROW]
[ROW][C]Residual SD (orginial)[/C][C]11.0604711505628[/C][/ROW]
[ROW][C]Residual SD (transformed)[/C][C]11.04155646964[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31014&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31014&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 correlation0.58178127280028
optimal lambda(x)-0.23
Residual SD (orginial)11.0604711505628
Residual SD (transformed)11.04155646964


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')