modelu Classical Deomposition, Time Series Analysis (new) - Goudkoers te brussel

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 25 May 2008 14:43:54 -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/25/t12117483137u60zfpzef6oxys.htm/, Retrieved Sun, 25 May 2008 22:45:13 +0200

User-defined keywords:

Dataseries X:

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10236 10893 10756 10940 10997 10827 10166 10186 10457 10368 10244 10511 10812 10738 10171 9721 9897 9828 9924 10371 10846 10413 10709 10662 10570 10297 10635 10872 10296 10383 10431 10574 10653 10805 10872 10625 10407 10463 10556 10646 10702 11353 11346 11451 11964 12574 13031 13812 14544 14931 14886 16005 17064 15168 16050 15839 15137 14954 15648 15305 15579 16348 15928 16171 15937 15713 15594 15683 16438 17032 17696 17745

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 6 seconds R Server 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 10236 NA NA 1.01819897956463 NA 2 10893 NA NA 1.00880699491598 NA 3 10756 NA NA 0.996214706433282 NA 4 10940 NA NA 1.00424184529926 NA 5 10997 NA NA 1.00530698344173 NA 6 10827 NA NA 0.980623016160316 NA 7 10166 10469.6935323602 10572.4166666667 0.990283854907998 0.970993082899556 8 10186 10537.7918878506 10589.9583333333 0.995073970657797 0.966616166688942 9 10457 10547.0386334974 10559.125 0.9988553628731 0.991463136087181 10 10368 10392.0038156680 10483.9583333333 0.991229026791055 0.997690164852348 11 10244 10485.4444016680 10387.3333333333 1.00944526041345 0.976973374478094 12 10511 10317.5907699766 10299.875 1.0017199985414 1.01874558066271 13 10812 10434.6728424083 10248.1666666667 1.01819897956463 1.03616089965544 14 10738 10336.0263017852 10245.7916666667 1.00880699491598 1.03889054521324 15 10171 10230.8344724471 10269.7083333333 0.996214706433282 0.994151555026304 16 9721 10331.4308873877 10287.7916666667 1.00424184529926 0.94091516518463 17 9897 10363.7515800918 10309.0416666667 1.00530698344173 0.95496306752582 18 9828 10134.4528569705 10334.7083333333 0.980623016160316 0.969761282498866 19 9924 10230.5399814000 10330.9166666667 0.990283854907998 0.970036774016106 20 10371 10251.7081212865 10302.4583333333 0.995073970657797 1.01163629292818 21 10846 10291.6229934161 10303.4166666667 0.9988553628731 1.05386682031965 22 10413 10279.7471283839 10370.7083333333 0.991229026791055 1.01296266045769 23 10709 10533.8557139486 10435.2916666667 1.00944526041345 1.01662679751911 24 10662 10493.0587230544 10475.0416666667 1.0017199985414 1.01610028890569 25 10570 10710.7320407427 10519.2916666667 1.01819897956463 0.986860651521539 26 10297 10641.7788884943 10548.875 1.00880699491598 0.967601385810877 27 10635 10509.3595007874 10549.2916666667 0.996214706433282 1.01195510527575 28 10872 10602.3669685674 10557.5833333333 1.00424184529926 1.02543139963293 29 10296 10636.8599772601 10580.7083333333 1.00530698344173 0.96795483084399 30 10383 10380.8343897808 10585.9583333333 0.980623016160316 1.00020861619962 31 10431 10474.8512607712 10577.625 0.990283854907998 0.995813662678397 32 10574 10525.6436931255 10577.75 0.995073970657797 1.00459414248518 33 10653 10569.2631653213 10581.375 0.9988553628731 1.00792267477580 34 10805 10475.9691744791 10568.6666666667 0.991229026791055 1.03140815136441 35 10872 10676.0613150094 10576.1666666667 1.00944526041345 1.01835308726779 36 10625 10651.7896044900 10633.5 1.0017199985414 0.997484966800443 37 10407 10906.9898940538 10712.0416666667 1.01819897956463 0.954158764341901 38 10463 10881.7068187851 10786.7083333333 1.00880699491598 0.96152195370102 39 10556 10836.6990497429 10877.875 0.996214706433282 0.974097365954848 40 10646 11052.8949664148 11006.2083333333 1.00424184529926 0.963186570789718 41 10702 11229.1533416712 11169.875 1.00530698344173 0.95305493427408 42 11353 11171.8702894834 11392.625 0.980623016160316 1.01621301588930 43 11346 11584.1342255773 11697.7916666667 0.990283854907998 0.979443070933042 44 11451 11996.9434815740 12056.3333333333 0.995073970657797 0.9544931188171 45 11964 12408.6969350256 12422.9166666667 0.9988553628731 0.964162479158438 46 12574 12714.1230157638 12826.625 0.991229026791055 0.98897894761675 47 13031 13440.7636424051 13315 1.00944526041345 0.969513365958442 48 13812 13762.6727982936 13739.0416666667 1.0017199985414 1.00358412950953 49 14544 14350.4964179839 14094 1.01819897956463 1.01348410371181 50 14931 14600.2955029198 14472.8333333333 1.00880699491598 1.02265053450556 51 14886 14731.8985518971 14787.875 0.996214706433282 1.01046039297380 52 16005 15082.9593350109 15019.25 1.00424184529926 1.06113128362342 53 17064 15308.2702025680 15227.4583333333 1.00530698344173 1.11469158658681 54 15168 15100.3278108063 15398.7083333333 0.980623016160316 1.00448150464292 55 16050 15353.4021483209 15504.0416666667 0.990283854907998 1.04537091160315 56 15839 15529.3316931628 15606.2083333333 0.995073970657797 1.01994086500023 57 15137 15690.6859435859 15708.6666666667 0.9988553628731 0.96471244497681 58 14954 15620.7782332002 15759 0.991229026791055 0.957314659791849 59 15648 15867.4279882198 15718.9583333333 1.00944526041345 0.986171168485356 60 15305 15721.7032087744 15694.7083333333 1.0017199985414 0.973495034015029 61 15579 15984.1118307804 15698.4166666667 1.01819897956463 0.974655343063836 62 16348 15810.9479640685 15672.9166666667 1.00880699491598 1.03396709907287 63 15928 15661.1178193227 15720.625 0.996214706433282 1.01704106844455 64 16171 15928.6983423938 15861.4166666667 1.00424184529926 1.01521164205623 65 15937 16118.4219678491 16033.3333333333 1.00530698344173 0.98874443365418 66 15713 15906.0321964590 16220.3333333333 0.980623016160316 0.9878642144015 67 15594 NA NA 0.990283854907998 NA 68 15683 NA NA 0.995073970657797 NA 69 16438 NA NA 0.9988553628731 NA 70 17032 NA NA 0.991229026791055 NA 71 17696 NA NA 1.00944526041345 NA 72 17745 NA NA 1.0017199985414 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/1773t1211748227.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/1773t1211748227.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/2yr2x1211748227.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/2yr2x1211748227.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/3dcj71211748227.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/3dcj71211748227.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/4pu281211748227.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117483137u60zfpzef6oxys/4pu281211748227.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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