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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_decompose.wasp
Title produced by softwareClassical Decomposition
Date of computationTue, 17 Jan 2012 07:52:03 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Jan/17/t1326804732tnwb1va8e3y0fgx.htm/, Retrieved Wed, 01 May 2024 19:20:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=161212, Retrieved Wed, 01 May 2024 19:20:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact176

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2011-11-10 19:09:34] [14511500b645ce5186c706473940fe45]
- RMP     [Classical Decomposition] [] [2012-01-17 12:52:03] [87b6e955a128bfb8d1e350b3ce0d281e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
'B'	'B'
'A'	'C'
'D'	'A'
'D'	'B'
'A'	'A'
'A'	'B'
'B'	'A'
'B'	'C'
'B'	'D'
'B'	'B'
'A'	'D'
'A'	'D'
'D'	'A'
'A'	'A'
'A'	'D'
'B'	'A'
'B'	'A'
'A'	'C'
'B'	'D'
'A'	'B'
'A'	'D'
'D'	'A'
'B'	'B'
'D'	'A'
'A'	'C'
'D'	'D'
'A'	'C'
'B'	'A'
'B'	'A'
'D'	'B'
'A'	'D'
'C'	'A'
'A'	'D'
'B'	'C'
'B'	'B'
'A'	'D'
'D'	'A'
'B'	'B'
'A'	'D'
'C'	'D'
'B'	'D'
'A'	'A'
'A'	'D'
'D'	'A'
'D'	'C'
'D'	'B'
'B'	'D'
'B'	'C'
'A'	'A'
'C'	'C'
'A'	'D'
'B'	'A'
'D'	'A'
'D'	'A'
'D'	'C'
'B'	'B'
'A'	'B'
'B'	'D'
'D'	'D'
'D'	'A'
'D'	'A'
'C'	'B'
'D'	'B'
'B'	'A'
'B'	'B'
'D'	'C'
'D'	'A'
'D'	'B'
'B'	'B'
'B'	'A'
'B'	'B'
'A'	'A'
'B'	'B'
'B'	'D'
'C'	'C'
'D'	'A'
'A'	'B'
'C'	'A'
'B'	'B'
'C'	'D'
'B'	'C'
'A'	'D'
'B'	'D'
'A'	'B'
'B'	'B'
'B'	'B'
'B'	'B'
'B'	'B'
'C'	'A'
'D'	'A'
'A'	'B'
'C'	'A'
'B'	'B'
'B'	'A'
'C'	'D'
'A'	'C'
'D'	'A'
'B'	'C'
'A'	'C'
'B'	'D'
'A'	'D'
'D'	'A'
'A'	'B'
'D'	'C'
'B'	'A'
'D'	'A'
'A'	'C'
'B'	'A'
'D'	'A'
'D'	'A'
'B'	'A'
'D'	'A'
'C'	'C'
'B'	'A'
'A'	'B'
'A'	'D'
'B'	'A'
'B'	'B'
'B'	'D'
'B'	'A'
'D'	'A'
'B'	'A'
'B'	'C'
'B'	'D'
'B'	'C'
'C'	'C'
'A'	'D'
'A'	'D'
'A'	'C'
'B'	'B'
'C'	'C'
'D'	'A'
'B'	'D'
'B'	'A'
'B'	'B'
'A'	'A'
'D'	'A'
'B'	'A'
'D'	'A'
'B'	'C'
'C'	'B'
'B'	'D'
'A'	'A'
'B'	'B'
'B'	'B'
'A'	'C'
'A'	'B'
'D'	'B'
'D'	'C'
'D'	'A'
'A'	'B'
'C'	'A'
'A'	'D'
'D'	'B'
'D'	'A'
'C'	'A'
'C'	'A'
'B'	'A'
'A'	'C'
'C'	'D'
'D'	'A'
'C'	'A'

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'Gertrude Mary Cox' @ cox.wessa.net

\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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=161212&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=161212&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=161212&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'Gertrude Mary Cox' @ cox.wessa.net


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = additive ; par2 = 12 ;
Parameters (R input):
par1 = additive ; par2 = 12 ;
R code (references can be found in the software module):
par2 <- as.numeric(par2)
x <- ts(x,freq=par2)
m <- decompose(x,type=par1)
m$figure
bitmap(file='test1.png')
plot(m)
dev.off()
mylagmax <- length(x)/2
bitmap(file='test2.png')
op <- par(mfrow = c(2,2))
acf(as.numeric(x),lag.max = mylagmax,main='Observed')
acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend')
acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random')
par(op)
dev.off()
bitmap(file='test3.png')
op <- par(mfrow = c(2,2))
spectrum(as.numeric(x),main='Observed')
spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
bitmap(file='test4.png')
op <- par(mfrow = c(2,2))
cpgram(as.numeric(x),main='Observed')
cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend')
cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal')
cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random')
par(op)
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'t',header=TRUE)
a<-table.element(a,'Observations',header=TRUE)
a<-table.element(a,'Fit',header=TRUE)
a<-table.element(a,'Trend',header=TRUE)
a<-table.element(a,'Seasonal',header=TRUE)
a<-table.element(a,'Random',header=TRUE)
a<-table.row.end(a)
for (i in 1:length(m$trend)) {
a<-table.row.start(a)
a<-table.element(a,i,header=TRUE)
a<-table.element(a,x[i])
if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i])
a<-table.element(a,m$trend[i])
a<-table.element(a,m$seasonal[i])
a<-table.element(a,m$random[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')