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*The author of this computation has been verified*
R Software Module: /rwasp_decompose.wasp (opens new window with default values)
Title produced by software: Classical Decomposition
Date of computation: Sat, 25 Dec 2010 16:14:48 +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/Dec/25/t1293294335070a6rv5wuk98u5.htm/, Retrieved Sat, 25 Dec 2010 17:25:35 +0100
 
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/Dec/25/t1293294335070a6rv5wuk98u5.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:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
5.2 7.9 8.7 8.9 15.3 15.4 18.1 19.7 13 12.6 6.2 3.5 3.4 0 9.5 8.9 10.4 13.2 18.9 19 16.3 10.6 5.8 3.6 2.6 5 7.3 9.2 15.7 16.8 18.4 18.1 14.6 7.8 7.6 3.8 5.6 2.2 6.8 11.8 14.9 16.7 16.7 15.9 13.6 9.2 2.8 2.5 4.8 2.8 7.8 9 12.9 16.4 21.8 17.8 13.5 10 10.4 5.5 4 6.8 5.7 9.1 13.6 15 20.9 20.4 14 13.7 7.1 0.8 2.1 1.3 3.9 10.7 11.1 16.4 17.1 17.3 12.9 10.9 5.3 0.7 -0.2 6.5 8.6 8.5 13.3 16.2 17.5 21.2 14.8 10.3 7.3 5.1 4.4 6.2 7.7 9.3 15.6 16.3 16.6 17.4 15.3 9.7 3.7 4.6 5.4 3.1 7.9 10.1 15 15.6 19.7 18.1 17.7 10.7 6.2 4.2 4 5.9 7.1 10.5 15.1 16.8 15.3 18.4 16.1 11.3 7.9 5.6 3.4 4.8 6.5 8.5 15.1 15.7 18.7 19.2 12.9 14.4 6.2 3.3 4.6 7.2 7.8 9.9 13.6 17.1 17.8 18.6 14.7 10.5 8.6 4.4 2.3 2.8 8.8 10.7 13.9 19.3 19.5 20.4 15.3 7.9 8.3 4.5 3.2 5 6.6 11.1 12.8 16.3 17.4 18.9 15.8 11.7 6.4 2.9 4.7 2.4 7.2 10.7 13.4 18.5 18.3 16.8 16.6 14. etc...
 
Output produced by software:


Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24


Classical Decomposition by Moving Averages
tObservationsFitTrendSeasonalRandom
15.2NANA-7.04760599415205NA
27.9NANA-6.50089546783626NA
38.7NANA-3.66953581871345NA
48.9NANA-0.583351608187134NA
515.3NANA3.23287646198830NA
615.4NANA5.73704312865497NA
718.118.829367690058511.13333333333337.69603435672515-0.729367690058478
819.718.307657163742710.72916666666677.578490497076021.39234283625731
91314.620376461988310.43333333333334.18704312865497-1.62037646198830
1012.610.808095760233910.46666666666670.3414290935672511.79190423976608
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123.52.970157163742699.96666666666667-6.996509502923980.529842836257311
133.42.860727339181289.90833333333333-7.047605994152050.539272660818716
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159.56.3512975146198810.0208333333333-3.669535818713453.14870248538012
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1813.215.69954312865509.96255.73704312865497-2.49954312865497
1918.917.62936769005859.933333333333337.696034356725151.27063230994152
201917.686823830409410.10833333333337.578490497076021.31317616959064
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3016.816.303709795321610.56666666666675.737043128654970.496290204678363
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753.95.909630847953229.57916666666667-3.66953581871345-2.00963084795322
7610.78.833315058479539.41666666666667-0.5833516081871341.86668494152047
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7816.414.88287646198839.145833333333335.737043128654971.51712353801170
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878.66.5262975146198810.1958333333333-3.669535818713452.07370248538012
888.59.6666483918128710.25-0.583351608187134-1.16664839181287
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9016.216.312043128655010.5755.73704312865497-0.112043128654971
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20914.615.003709795321611.77083333333333.23287646198830-0.403709795321637
21017.517.337043128655011.65.737043128654970.162956871345031
21117.219.191867690058511.49583333333337.69603435672515-1.99186769005848
21217.219.015990497076011.43757.57849049707602-1.81599049707602
21314.115.524543128655011.33754.18704312865497-1.42454312865497
21410.511.399762426900611.05833333333330.341429093567251-0.899762426900585
2156.86.949981725146210.925-3.9750182748538-0.149981725146198
2164.13.9451571637426910.9416666666667-6.996509502923980.154842836257311
2176.53.8690606725146210.9166666666667-7.047605994152052.63093932748538
2186.14.4657711988304110.9666666666667-6.500895467836261.63422880116959
2196.37.3096308479532210.9791666666667-3.66953581871345-1.00963084795322
2209.310.391648391812910.975-0.583351608187134-1.09164839181286
22116.414.212043128655010.97916666666673.232876461988302.18795687134503
22216.116.666209795321610.92916666666675.73704312865497-0.566209795321635
2231818.329367690058510.63333333333337.69603435672515-0.329367690058481
22417.617.865990497076010.28757.57849049707602-0.265990497076023
2251414.387043128655010.24.18704312865497-0.387043128654970
22610.510.691429093567310.350.341429093567251-0.191429093567251
2276.96.424981725146210.4-3.97501827485380.475018274853801
2282.83.3368238304093610.3333333333333-6.99650950292398-0.536823830409357
2290.73.3315606725146210.3791666666667-7.04760599415205-2.63156067251462
2303.63.9824378654970710.4833333333333-6.50089546783626-0.382437865497074
2316.76.9637975146198810.6333333333333-3.66953581871345-0.263797514619883
23212.510.158315058479510.7416666666667-0.5833516081871342.34168494152047
23314.414.124543128655010.89166666666673.232876461988300.275456871345032
23416.516.749543128655011.01255.73704312865497-0.249543128654970
23518.7NANA7.69603435672515NA
23619.4NANA7.57849049707602NA
23715.8NANA4.18704312865497NA
23811.3NANA0.341429093567251NA
2399.7NANA-3.9750182748538NA
2402.9NANA-6.99650950292398NA
 
Charts produced by software:
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/14np01293293682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/14np01293293682.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/24np01293293682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/24np01293293682.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/3eeol1293293682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/3eeol1293293682.ps (open in new window)


http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/4pooo1293293682.png (open in new window)
http://www.freestatistics.org/blog/date/2010/Dec/25/t1293294335070a6rv5wuk98u5/4pooo1293293682.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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