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opgave 9 oefening 2 Patrick Fieremans

*Unverified author*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Mon, 24 May 2010 21:00:11 +0000
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084.htm/, Retrieved Mon, 24 May 2010 23:02:39 +0200
 
BibTeX entries for LaTeX users:
@Manual{KEY,
    author = {{YOUR NAME}},
    publisher = {Office for Research Development and Education},
    title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084.htm/},
    year = {2010},
}
@Manual{R,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Development Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2010},
    note = {{ISBN} 3-900051-07-0},
    url = {http://www.R-project.org},
}
 
Original text written by user:
 
IsPrivate?
No (this computation is public)
 
User-defined keywords:
KDGP2W52
 
Dataseries X:
» Textbox « » Textfile « » CSV «
93,2 96 95,2 77,1 70,9 64,8 70,1 77,3 79,5 100,6 100,7 107,1 95,9 82,8 83,3 80 80,4 67,5 75,7 71,1 89,3 101,1 105,2 114,1 96,3 84,4 91,2 81,9 80,5 70,4 74,8 75,9 86,3 98,7 100,9 113,8 89,8 84,4 87,2 85,6 72 69,2 77,5 78,1 94,3 97,7 100,2 116,4 97,1 93 96 80,5 76,1 69,9 73,6 92,6 94,2 93,5 108,5 109,4 105,1 92,5 97,1 81,4 79,1 72,1 78,7 87,1 91,4 109,9 116,3 113 100 84,8 94,3 87,1 90,3 72,4 84,9 92,7 92,2 114,9 112,5 118,3 106 91,2 96,6 96,3 88,2 70,2 86,5 88,2 102,8 119,1 119,2 125,1 106,1 102,1 105,2 101 84,3 87,5 92,7 94,4 113 113,9 122,9 132,7 106,9 96,6 127,3 98,2 100,2 89,4 95,3 104,2 106,4 116,2 135,9 134 104,6 107,1 123,5 98,8 98,6 90,6 89,1 105,2 114 122,1 138 142,2 116,4 112,6 123,8 103,6 113,9 98,6 95 116 113,9 127,5 131,4 145,9 131,5 131 130,5 118,9 114,3 85,7 104,6 105,1 117,3 142,5 140 159,8 131,2 125,4 126,5 119,4 113,5 98,7 114,5 113, etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
193.2NANA3.92258771929825NA
296NANA-5.40657894736841NA
395.2NANA6.13859649122807NA
477.1NANA-7.39616228070176NA
570.9NANA-11.5802631578947NA
664.8NANA-25.1287280701754NA
770.170.599780701754486.1541666666667-15.5543859649123-0.499780701754403
877.376.173574561403585.7166666666667-9.543092105263161.12642543859648
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10100.697.681688596491284.295833333333313.38585526315792.91831140350877
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451128132.862280701754148.416666666667-15.5543859649123-4.86228070175434
452140138.998574561404148.541666666667-9.543092105263161.00142543859647
453143142.533771929825148.75-6.216228070175440.466228070175418
454151161.552521929825148.16666666666713.3858552631579-10.5525219298245
455177169.451644736842146.7522.70164473684217.5483552631579
456184181.010087719298146.33333333333334.67675438596492.98991228070179
457151150.047587719298146.1253.922587719298250.952412280701793
458134140.801754385965146.208333333333-5.40657894736841-6.8017543859649
459164152.471929824561146.3333333333336.1385964912280711.5280701754386
460126139.312171052632146.708333333333-7.39616228070176-13.3121710526316
461131136.044736842105147.625-11.5802631578947-5.04473684210527
462125122.954605263158148.083333333333-25.12872807017542.0453947368421
463127131.903947368421147.458333333333-15.5543859649123-4.90394736842103
464143137.456907894737147-9.543092105263165.54309210526316
465143140.367105263158146.583333333333-6.216228070175442.63289473684210
466160159.510855263158146.12513.38585526315790.489144736842121
467190169.70164473684214722.701644736842120.2983552631579
468182182.718421052632148.04166666666734.6767543859649-0.718421052631584
469138NA147.916666666667NANA
470136NA148NANA
471152NANANANA
472127NANANANA
473151NANANANA
474130NANANANA
475119NANANANA
476153NANANANA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/1kj3e1274734802.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/1kj3e1274734802.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/2kj3e1274734802.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/2kj3e1274734802.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/3us2h1274734802.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/3us2h1274734802.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/4nkjk1274734802.png (open in new window)
http://www.freestatistics.org/blog/date/2010/May/24/t1274734953y043hiyyrubs084/4nkjk1274734802.ps (open in new window)


 
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')
 





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Software written by Ed van Stee & Patrick Wessa


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