decompositie

R Software Module: rwasp_decompose.wasp (opens new window with default values)

Title produced by software: Classical Decomposition

Date of computation: Mon, 19 May 2008 11:55:37 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s.htm/, Retrieved Mon, 19 May 2008 19:58:02 +0200

User-defined keywords:

Dataseries X:

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16.100 15.800 16.900 17.800 17.600 18.300 18.000 15.700 14.500 14.000 15.500 15.800 15.800 15.900 18.000 19.900 20.600 20.600 20.800 20.000 18.500 17.700 17.000 16.600 16.700 17.300 19.100 20.200 20.700 21.500 21.000 16.800 16.800 16.500 17.200 17.300 17.600 18.400 19.900 20.500 21.200 21.300 20.800 18.800 18.100 18.100 18.800 18.700 18.700 19.000 20.100 20.500 21.600 21.800 21.500 21.200 20.400 20.400 20.600 19.300 18.600 19.400 23.500 24.600 25.900 26.600 24.100 21.800 21.300 21.100 21.200 21.600

Text written by user:

Output produced by software:

Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 2 seconds R Server 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 16.1 NA NA -1.40425347222222 NA 2 15.8 NA NA -1.04800347222222 NA 3 16.9 NA NA 0.458246527777778 NA 4 17.8 NA NA 1.33012152777777 NA 5 17.6 NA NA 1.96032986111111 NA 6 18.3 NA NA 2.14574652777778 NA 7 18 18.1259548611111 16.3208333333333 1.80512152777778 -0.125954861111111 8 15.7 16.2269965277778 16.3125 -0.0855034722222209 -0.526996527777779 9 14.5 15.4332465277778 16.3625 -0.929253472222222 -0.93324652777778 10 14 15.1853298611111 16.4958333333333 -1.31050347222222 -1.18532986111111 11 15.5 15.5186631944444 16.7083333333333 -1.18967013888889 -0.0186631944444429 12 15.8 15.1967881944444 16.9291666666667 -1.73237847222222 0.60321180555556 13 15.8 15.7374131944444 17.1416666666667 -1.40425347222222 0.0625868055555578 14 15.9 16.3894965277778 17.4375 -1.04800347222222 -0.489496527777774 15 18 18.2415798611111 17.7833333333333 0.458246527777778 -0.241579861111113 16 19.9 19.4342881944444 18.1041666666667 1.33012152777777 0.465711805555557 17 20.6 20.2811631944444 18.3208333333333 1.96032986111111 0.318836805555559 18 20.6 20.5624131944444 18.4166666666667 2.14574652777778 0.0375868055555557 19 20.8 20.2926215277778 18.4875 1.80512152777778 0.507378472222225 20 20 18.4978298611111 18.5833333333333 -0.0855034722222209 1.50217013888889 21 18.5 17.7582465277778 18.6875 -0.929253472222222 0.741753472222221 22 17.7 17.4353298611111 18.7458333333333 -1.31050347222222 0.264670138888892 23 17 17.5728298611111 18.7625 -1.18967013888889 -0.572829861111106 24 16.6 17.0717881944444 18.8041666666667 -1.73237847222222 -0.471788194444443 25 16.7 17.4457465277778 18.85 -1.40425347222222 -0.74574652777778 26 17.3 17.6769965277778 18.725 -1.04800347222222 -0.376996527777777 27 19.1 18.9790798611111 18.5208333333333 0.458246527777778 0.120920138888891 28 20.2 19.7301215277778 18.4 1.33012152777777 0.469878472222224 29 20.7 20.3186631944444 18.3583333333333 1.96032986111111 0.381336805555556 30 21.5 20.5415798611111 18.3958333333333 2.14574652777778 0.95842013888889 31 21 20.2676215277778 18.4625 1.80512152777778 0.732378472222223 32 16.8 18.4603298611111 18.5458333333333 -0.0855034722222209 -1.66032986111111 33 16.8 17.6957465277778 18.625 -0.929253472222222 -0.895746527777778 34 16.5 17.3603298611111 18.6708333333333 -1.31050347222222 -0.860329861111111 35 17.2 17.5144965277778 18.7041666666667 -1.18967013888889 -0.314496527777781 36 17.3 16.9842881944444 18.7166666666667 -1.73237847222222 0.315711805555559 37 17.6 17.2957465277778 18.7 -1.40425347222222 0.304253472222225 38 18.4 17.7269965277778 18.775 -1.04800347222222 0.673003472222224 39 19.9 19.3707465277778 18.9125 0.458246527777778 0.529253472222223 40 20.5 20.3634548611111 19.0333333333333 1.33012152777777 0.136545138888891 41 21.2 21.1269965277778 19.1666666666667 1.96032986111111 0.0730034722222221 42 21.3 21.4374131944444 19.2916666666667 2.14574652777778 -0.137413194444445 43 20.8 21.2009548611111 19.3958333333333 1.80512152777778 -0.400954861111114 44 18.8 19.3811631944444 19.4666666666667 -0.0855034722222209 -0.58116319444444 45 18.1 18.5707465277778 19.5 -0.929253472222222 -0.470746527777774 46 18.1 18.1978298611111 19.5083333333333 -1.31050347222222 -0.097829861111105 47 18.8 18.3353298611111 19.525 -1.18967013888889 0.464670138888895 48 18.7 17.8301215277778 19.5625 -1.73237847222222 0.869878472222222 49 18.7 18.2082465277778 19.6125 -1.40425347222222 0.491753472222221 50 19 18.6936631944444 19.7416666666667 -1.04800347222222 0.306336805555553 51 20.1 20.3957465277778 19.9375 0.458246527777778 -0.295746527777776 52 20.5 21.4592881944444 20.1291666666667 1.33012152777777 -0.95928819444444 53 21.6 22.2603298611111 20.3 1.96032986111111 -0.660329861111116 54 21.8 22.5457465277778 20.4 2.14574652777778 -0.745746527777776 55 21.5 22.2259548611111 20.4208333333333 1.80512152777778 -0.72595486111111 56 21.2 20.3478298611111 20.4333333333333 -0.0855034722222209 0.85217013888889 57 20.4 19.6624131944444 20.5916666666667 -0.929253472222222 0.737586805555555 58 20.4 19.5936631944444 20.9041666666667 -1.31050347222222 0.806336805555553 59 20.6 20.0644965277778 21.2541666666667 -1.18967013888889 0.535503472222224 60 19.3 19.9009548611111 21.6333333333333 -1.73237847222222 -0.600954861111113 61 18.6 20.5374131944444 21.9416666666667 -1.40425347222222 -1.93741319444444 62 19.4 21.0269965277778 22.075 -1.04800347222222 -1.62699652777778 63 23.5 22.5957465277778 22.1375 0.458246527777778 0.904253472222223 64 24.6 23.5342881944444 22.2041666666667 1.33012152777777 1.06571180555556 65 25.9 24.2186631944444 22.2583333333333 1.96032986111111 1.68133680555555 66 26.6 24.5249131944444 22.3791666666667 2.14574652777778 2.07508680555556 67 24.1 NA NA 1.80512152777778 NA 68 21.8 NA NA -0.0855034722222209 NA 69 21.3 NA NA -0.929253472222222 NA 70 21.1 NA NA -1.31050347222222 NA 71 21.2 NA NA -1.18967013888889 NA 72 21.6 NA NA -1.73237847222222 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/1rcwu1211219735.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/1rcwu1211219735.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/2wyqy1211219735.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/2wyqy1211219735.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/3ujse1211219735.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/3ujse1211219735.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/488mz1211219735.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t12112198772vm14dklsk2oj1s/488mz1211219735.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')

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

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