Yelle Eyckmans

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 07 Jun 2009 03:14:45 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h.htm/, Retrieved Sun, 07 Jun 2009 11:17:45 +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/2009/Jun/07/t1244366265l3yffyfwhttls0h.htm/}, year = {2009}, } @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 = {2009}, 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 «

10,812 10,738 10,171 9,721 9,897 9,828 9,924 10,371 10,846 10,413 10,709 10,662 10,57 10,297 10,635 10,872 10,296 10,383 10,431 10,574 10,653 10,805 10,872 10,625 10,407 10,463 10,556 10,646 10,702 11,353 11,346 11,451 11,964 12,574 13,031 13,812 14,544 14,931 14,886 16,005 17,064 15,168 16,05 15,839 15,137 14,954 15,648 15,305 15,579 16,348 15,928 16,171 15,937 15,713 15,594 15,683 16,438 17,032 17,696 17,745 19,394 20,148 20,108 18,584 18,441 18,391 19,178 18,079 18,483 19,644 19,195 19,65 20,83

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 10.812 NA NA 0.269561111111111 NA 2 10.738 NA NA 0.466811111111111 NA 3 10.171 NA NA 0.324136111111111 NA 4 9.721 NA NA 0.216569444444444 NA 5 9.897 NA NA 0.101327777777778 NA 6 9.828 NA NA -0.33068888888889 NA 7 9.924 10.1580277777778 10.3309166666667 -0.172888888888889 -0.234027777777776 8 10.371 9.91571111111111 10.3024583333333 -0.386747222222222 0.455288888888889 9 10.846 9.97972777777778 10.3034166666667 -0.323688888888889 0.866272222222221 10 10.413 10.2332194444444 10.3707083333333 -0.137488888888888 0.179780555555554 11 10.709 10.4420027777778 10.4352916666667 0.00671111111111208 0.266997222222219 12 10.662 10.4414277777778 10.4750416666667 -0.0336138888888883 0.220572222222224 13 10.57 10.7888527777778 10.5192916666667 0.269561111111111 -0.218852777777778 14 10.297 11.0156861111111 10.548875 0.466811111111111 -0.718686111111111 15 10.635 10.8734277777778 10.5492916666667 0.324136111111111 -0.238427777777778 16 10.872 10.7741527777778 10.5575833333333 0.216569444444444 0.0978472222222226 17 10.296 10.6820361111111 10.5807083333333 0.101327777777778 -0.38603611111111 18 10.383 10.2552694444444 10.5859583333333 -0.33068888888889 0.127730555555557 19 10.431 10.4047361111111 10.577625 -0.172888888888889 0.026263888888888 20 10.574 10.1910027777778 10.57775 -0.386747222222222 0.382997222222222 21 10.653 10.2576861111111 10.581375 -0.323688888888889 0.395313888888888 22 10.805 10.4311777777778 10.5686666666667 -0.137488888888888 0.373822222222222 23 10.872 10.5828777777778 10.5761666666667 0.00671111111111208 0.289122222222222 24 10.625 10.5998861111111 10.6335 -0.0336138888888883 0.0251138888888889 25 10.407 10.9816027777778 10.7120416666667 0.269561111111111 -0.574602777777777 26 10.463 11.2535194444444 10.7867083333333 0.466811111111111 -0.790519444444445 27 10.556 11.2020111111111 10.877875 0.324136111111111 -0.646011111111113 28 10.646 11.2227777777778 11.0062083333333 0.216569444444444 -0.576777777777776 29 10.702 11.2712027777778 11.169875 0.101327777777778 -0.569202777777777 30 11.353 11.0619361111111 11.392625 -0.33068888888889 0.291063888888887 31 11.346 11.5249027777778 11.6977916666667 -0.172888888888889 -0.178902777777777 32 11.451 11.6695861111111 12.0563333333333 -0.386747222222222 -0.218586111111112 33 11.964 12.0992277777778 12.4229166666667 -0.323688888888889 -0.135227777777777 34 12.574 12.6891361111111 12.826625 -0.137488888888888 -0.115136111111111 35 13.031 13.3217111111111 13.315 0.00671111111111208 -0.290711111111111 36 13.812 13.7054277777778 13.7390416666667 -0.0336138888888883 0.106572222222223 37 14.544 14.3635611111111 14.094 0.269561111111111 0.180438888888892 38 14.931 14.9396444444444 14.4728333333333 0.466811111111111 -0.00864444444444246 39 14.886 15.1120111111111 14.787875 0.324136111111111 -0.226011111111109 40 16.005 15.2358194444444 15.01925 0.216569444444444 0.76918055555556 41 17.064 15.3287861111111 15.2274583333333 0.101327777777778 1.73521388888889 42 15.168 15.0680194444444 15.3987083333333 -0.33068888888889 0.0999805555555575 43 16.05 15.3311527777778 15.5040416666667 -0.172888888888889 0.718847222222223 44 15.839 15.2194611111111 15.6062083333333 -0.386747222222222 0.61953888888889 45 15.137 15.3849777777778 15.7086666666667 -0.323688888888889 -0.247977777777777 46 14.954 15.6215111111111 15.759 -0.137488888888888 -0.667511111111112 47 15.648 15.7256694444444 15.7189583333333 0.00671111111111208 -0.0776694444444459 48 15.305 15.6610944444444 15.6947083333333 -0.0336138888888883 -0.356094444444444 49 15.579 15.9679777777778 15.6984166666667 0.269561111111111 -0.388977777777777 50 16.348 16.1397277777778 15.6729166666667 0.466811111111111 0.20827222222222 51 15.928 16.0447611111111 15.720625 0.324136111111111 -0.11676111111111 52 16.171 16.0779861111111 15.8614166666667 0.216569444444444 0.0930138888888887 53 15.937 16.1346611111111 16.0333333333333 0.101327777777778 -0.197661111111110 54 15.713 15.8896444444444 16.2203333333333 -0.33068888888889 -0.176644444444445 55 15.594 16.3080694444444 16.4809583333333 -0.172888888888889 -0.714069444444444 56 15.683 16.4115027777778 16.79825 -0.386747222222222 -0.728502777777777 57 16.438 16.8070611111111 17.13075 -0.323688888888889 -0.369061111111112 58 17.032 17.2679694444444 17.4054583333333 -0.137488888888888 -0.235969444444439 59 17.696 17.6170444444444 17.6103333333333 0.00671111111111208 0.0789555555555594 60 17.745 17.7926361111111 17.82625 -0.0336138888888883 -0.0476361111111068 61 19.394 18.3567277777778 18.0871666666667 0.269561111111111 1.03727222222222 62 20.148 18.8031444444444 18.3363333333333 0.466811111111111 1.34485555555556 63 20.108 18.8455111111111 18.521375 0.324136111111111 1.26248888888889 64 18.584 18.9319861111111 18.7154166666667 0.216569444444444 -0.347986111111112 65 18.441 18.9880361111111 18.8867083333333 0.101327777777778 -0.547036111111112 66 18.391 18.6978527777778 19.0285416666667 -0.33068888888889 -0.306852777777777 67 19.178 18.9948611111111 19.16775 -0.172888888888889 0.183138888888891 68 18.079 NA NA -0.386747222222222 NA 69 18.483 NA NA -0.323688888888889 NA 70 19.644 NA NA -0.137488888888888 NA 71 19.195 NA NA 0.00671111111111208 NA 72 19.65 NA NA -0.0336138888888883 NA 73 20.83 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/1fsxk1244366081.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/1fsxk1244366081.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/27mea1244366081.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/27mea1244366081.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/3cg131244366081.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/3cg131244366081.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/4ughh1244366081.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t1244366265l3yffyfwhttls0h/4ughh1244366081.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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