*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 16 May 2011 20:46:04 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz.htm/, Retrieved Mon, 16 May 2011 22:52:09 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

1,3014 1,3201 1,2938 1,2694 1,2165 1,2037 1,2292 1,2256 1,2015 1,1786 1,1856 1,2103 1,1938 1,202 1,2271 1,277 1,265 1,2684 1,2811 1,2727 1,2611 1,2881 1,3213 1,2999 1,3074 1,3242 1,3516 1,3511 1,3419 1,3716 1,3622 1,3896 1,4227 1,4684 1,457 1,4718 1,4748 1,5527 1,5751 1,5557 1,5553 1,577 1,4975 1,437 1,3322 1,2732 1,3449 1,3239 1,2785 1,305 1,319 1,365 1,4016 1,4088 1,4268 1,4562 1,4816 1,4914 1,4614 1,4272 1,3686 1,3569 1,3406 1,2565 1,2209 1,277 1,2894 1,3067 1,3898 1,3661 1,322 1,336

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 1 seconds R Server 'Herman Ole Andreas Wold' @ www.yougetit.org Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.3014 NA NA -0.0262893055555556 NA 2 1.3201 NA NA -0.00392680555555558 NA 3 1.2938 NA NA 0.0083481944444445 NA 4 1.2694 NA NA 0.0035965277777778 NA 5 1.2165 NA NA -0.00322263888888885 NA 6 1.2037 NA NA 0.0182131944444444 NA 7 1.2292 1.24381069444444 1.231825 0.0119856944444445 -0.0146106944444444 8 1.2256 1.23039986111111 1.22242083333333 0.0079790277777777 -0.0047998611111113 9 1.2015 1.20560319444444 1.21472083333333 -0.00911763888888879 -0.00410319444444451 10 1.1786 1.20297819444444 1.21225833333333 -0.00928013888888894 -0.0243781944444441 11 1.1856 1.21948652777778 1.21459583333333 0.00489069444444448 -0.0338865277777776 12 1.2103 1.21613569444444 1.2193125 -0.00317680555555564 -0.00583569444444465 13 1.1938 1.19788152777778 1.22417083333333 -0.0262893055555556 -0.00408152777777793 14 1.202 1.22436902777778 1.22829583333333 -0.00392680555555558 -0.0223690277777777 15 1.2271 1.24108986111111 1.23274166666667 0.0083481944444445 -0.0139898611111109 16 1.277 1.24338402777778 1.2397875 0.0035965277777778 0.033615972222222 17 1.265 1.24678152777778 1.25000416666667 -0.00322263888888885 0.0182184722222218 18 1.2684 1.27760486111111 1.25939166666667 0.0182131944444444 -0.00920486111111107 19 1.2811 1.27984402777778 1.26785833333333 0.0119856944444445 0.00125597222222207 20 1.2727 1.28566236111111 1.27768333333333 0.0079790277777777 -0.0129623611111109 21 1.2611 1.27884486111111 1.2879625 -0.00911763888888879 -0.0177448611111111 22 1.2881 1.28695736111111 1.2962375 -0.00928013888888894 0.0011426388888891 23 1.3213 1.30741986111111 1.30252916666667 0.00489069444444448 0.0138801388888889 24 1.2999 1.30685652777778 1.31003333333333 -0.00317680555555564 -0.00695652777777767 25 1.3074 1.29142319444444 1.3177125 -0.0262893055555556 0.0159768055555554 26 1.3242 1.32203569444444 1.3259625 -0.00392680555555558 0.00216430555555558 27 1.3516 1.34591486111111 1.33756666666667 0.0083481944444445 0.00568513888888877 28 1.3511 1.35540902777778 1.3518125 0.0035965277777778 -0.00430902777777753 29 1.3419 1.36175652777778 1.36497916666667 -0.00322263888888885 -0.0198565277777778 30 1.3716 1.39600902777778 1.37779583333333 0.0182131944444444 -0.0244090277777778 31 1.3622 1.40391902777778 1.39193333333333 0.0119856944444445 -0.0417190277777777 32 1.3896 1.41640819444444 1.40842916666667 0.0079790277777777 -0.0268081944444447 33 1.4227 1.41814486111111 1.4272625 -0.00911763888888879 0.00455513888888892 34 1.4684 1.43581986111111 1.4451 -0.00928013888888894 0.0325801388888887 35 1.457 1.46740736111111 1.46251666666667 0.00489069444444448 -0.0104073611111111 36 1.4718 1.47678986111111 1.47996666666667 -0.00317680555555564 -0.00498986111111099 37 1.4748 1.46787319444444 1.4941625 -0.0262893055555556 0.0069268055555558 38 1.5527 1.49784819444444 1.501775 -0.00392680555555558 0.0548518055555554 39 1.5751 1.50832736111111 1.49997916666667 0.0083481944444445 0.0667726388888887 40 1.5557 1.49167152777778 1.488075 0.0035965277777778 0.0640284722222224 41 1.5553 1.47204819444444 1.47527083333333 -0.00322263888888885 0.0832518055555556 42 1.577 1.48265069444444 1.4644375 0.0182131944444444 0.0943493055555558 43 1.4975 1.46208152777778 1.45009583333333 0.0119856944444445 0.0354184722222224 44 1.437 1.43957486111111 1.43159583333333 0.0079790277777777 -0.00257486111111094 45 1.3322 1.40148652777778 1.41060416666667 -0.00911763888888879 -0.0692865277777779 46 1.2732 1.38270736111111 1.3919875 -0.00928013888888894 -0.109507361111111 47 1.3449 1.38252819444444 1.3776375 0.00489069444444448 -0.0376281944444445 48 1.3239 1.36104819444444 1.364225 -0.00317680555555564 -0.0371481944444443 49 1.2785 1.32798152777778 1.35427083333333 -0.0262893055555556 -0.049481527777778 50 1.305 1.34819819444444 1.352125 -0.00392680555555558 -0.0431981944444446 51 1.319 1.36749819444444 1.35915 0.0083481944444445 -0.0484981944444445 52 1.365 1.37806319444444 1.37446666666667 0.0035965277777778 -0.0130631944444446 53 1.4016 1.38518986111111 1.3884125 -0.00322263888888885 0.0164101388888886 54 1.4088 1.41578402777778 1.39757083333333 0.0182131944444444 -0.00698402777777773 55 1.4268 1.41761486111111 1.40562916666667 0.0119856944444445 0.00918513888888883 56 1.4562 1.41952486111111 1.41154583333333 0.0079790277777777 0.0366751388888886 57 1.4816 1.40549069444444 1.41460833333333 -0.00911763888888879 0.0761093055555555 58 1.4914 1.40170736111111 1.4109875 -0.00928013888888894 0.089692638888889 59 1.4614 1.40382819444444 1.3989375 0.00489069444444448 0.0575718055555556 60 1.4272 1.38273986111111 1.38591666666667 -0.00317680555555564 0.044460138888889 61 1.3686 1.34841069444444 1.3747 -0.0262893055555556 0.0201893055555555 62 1.3569 1.35881902777778 1.36274583333333 -0.00392680555555558 -0.00191902777777786 63 1.3406 1.36103986111111 1.35269166666667 0.0083481944444445 -0.0204398611111112 64 1.2565 1.34724236111111 1.34364583333333 0.0035965277777778 -0.0907423611111113 65 1.2209 1.32939402777778 1.33261666666667 -0.00322263888888885 -0.108494027777778 66 1.277 1.34122152777778 1.32300833333333 0.0182131944444444 -0.0642215277777776 67 1.2894 NA NA 0.0119856944444445 NA 68 1.3067 NA NA 0.0079790277777777 NA 69 1.3898 NA NA -0.00911763888888879 NA 70 1.3661 NA NA -0.00928013888888894 NA 71 1.322 NA NA 0.00489069444444448 NA 72 1.336 NA NA -0.00317680555555564 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/1kna01305578763.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/1kna01305578763.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/2sazi1305578763.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/2sazi1305578763.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/3we2o1305578763.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/3we2o1305578763.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/4ilct1305578763.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305579126dj7ji18ak91qvoz/4ilct1305578763.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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