Elke Van Buggenhout - Goudprijs opgave9

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 09:41:10 -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/t121121179370dfwy6fkc1o6sj.htm/, Retrieved Mon, 19 May 2008 17:43:18 +0200

User-defined keywords:

Dataseries X:

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10.893 10.756 10.940 10.997 10.827 10.166 10.186 10.457 10.368 10.244 10.511 10.812 10.738 10.171 9.721 9.897 9.828 9.924 10.371 10.846 10.413 10.709 10.662 10.570 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 16.050 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

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 10.893 NA NA 0.125090277777777 NA 2 10.756 NA NA -0.0277951388888898 NA 3 10.94 NA NA 0.124684027777778 NA 4 10.997 NA NA 0.199371527777779 NA 5 10.827 NA NA -0.213607638888889 NA 6 10.166 NA NA -0.0584513888888892 NA 7 10.186 10.5444131944444 10.5899583333333 -0.0455451388888889 -0.358413194444443 8 10.457 10.4864236111111 10.559125 -0.0727013888888889 -0.0294236111111097 9 10.368 10.3206006944444 10.4839583333333 -0.163357638888888 0.0473993055555564 10 10.244 10.4723715277778 10.3873333333333 0.0850381944444442 -0.228371527777776 11 10.511 10.2966944444444 10.299875 -0.00318055555555515 0.214305555555557 12 10.812 10.2986215277778 10.2481666666667 0.0504548611111117 0.513378472222222 13 10.738 10.3708819444444 10.2457916666667 0.125090277777777 0.367118055555553 14 10.171 10.2419131944444 10.2697083333333 -0.0277951388888898 -0.0709131944444454 15 9.721 10.4124756944444 10.2877916666667 0.124684027777778 -0.691475694444447 16 9.897 10.5084131944444 10.3090416666667 0.199371527777779 -0.611413194444443 17 9.828 10.1211006944444 10.3347083333333 -0.213607638888889 -0.293100694444442 18 9.924 10.2724652777778 10.3309166666667 -0.0584513888888892 -0.348465277777777 19 10.371 10.2569131944444 10.3024583333333 -0.0455451388888889 0.114086805555555 20 10.846 10.2307152777778 10.3034166666667 -0.0727013888888889 0.615284722222222 21 10.413 10.2073506944444 10.3707083333333 -0.163357638888888 0.205649305555555 22 10.709 10.5203298611111 10.4352916666667 0.0850381944444442 0.188670138888888 23 10.662 10.4718611111111 10.4750416666667 -0.00318055555555515 0.190138888888891 24 10.57 10.5697465277778 10.5192916666667 0.0504548611111117 0.000253472222221163 25 10.297 10.6739652777778 10.548875 0.125090277777777 -0.376965277777778 26 10.635 10.5214965277778 10.5492916666667 -0.0277951388888898 0.113503472222222 27 10.872 10.6822673611111 10.5575833333333 0.124684027777778 0.189732638888888 28 10.296 10.7800798611111 10.5807083333333 0.199371527777779 -0.484079861111111 29 10.383 10.3723506944444 10.5859583333333 -0.213607638888889 0.0106493055555568 30 10.431 10.5191736111111 10.577625 -0.0584513888888892 -0.0881736111111131 31 10.574 10.5322048611111 10.57775 -0.0455451388888889 0.0417951388888884 32 10.653 10.5086736111111 10.581375 -0.0727013888888889 0.144326388888889 33 10.805 10.4053090277778 10.5686666666667 -0.163357638888888 0.399690972222222 34 10.872 10.6612048611111 10.5761666666667 0.0850381944444442 0.210795138888891 35 10.625 10.6303194444444 10.6335 -0.00318055555555515 -0.00531944444444399 36 10.407 10.7624965277778 10.7120416666667 0.0504548611111117 -0.355496527777778 37 10.463 10.9117986111111 10.7867083333333 0.125090277777777 -0.448798611111112 38 10.556 10.8500798611111 10.877875 -0.0277951388888898 -0.294079861111113 39 10.646 11.1308923611111 11.0062083333333 0.124684027777778 -0.484892361111111 40 10.702 11.3692465277778 11.169875 0.199371527777779 -0.667246527777777 41 11.353 11.1790173611111 11.392625 -0.213607638888889 0.173982638888887 42 11.346 11.6393402777778 11.6977916666667 -0.0584513888888892 -0.293340277777778 43 11.451 12.0107881944444 12.0563333333333 -0.0455451388888889 -0.559788194444446 44 11.964 12.3502152777778 12.4229166666667 -0.0727013888888889 -0.386215277777776 45 12.574 12.6632673611111 12.826625 -0.163357638888888 -0.0892673611111103 46 13.031 13.4000381944444 13.315 0.0850381944444442 -0.369038194444443 47 13.812 13.7358611111111 13.7390416666667 -0.00318055555555515 0.0761388888888899 48 14.544 14.1444548611111 14.094 0.0504548611111117 0.399545138888891 49 14.931 14.5979236111111 14.4728333333333 0.125090277777777 0.333076388888891 50 14.886 14.7600798611111 14.787875 -0.0277951388888898 0.125920138888890 51 16.005 15.1439340277778 15.01925 0.124684027777778 0.861065972222224 52 17.064 15.4268298611111 15.2274583333333 0.199371527777779 1.63717013888889 53 15.168 15.1851006944444 15.3987083333333 -0.213607638888889 -0.0171006944444425 54 16.05 15.4455902777778 15.5040416666667 -0.0584513888888892 0.604409722222226 55 15.839 15.5606631944444 15.6062083333333 -0.0455451388888889 0.278336805555558 56 15.137 15.6359652777778 15.7086666666667 -0.0727013888888889 -0.498965277777776 57 14.954 15.5956423611111 15.759 -0.163357638888888 -0.641642361111112 58 15.648 15.8039965277778 15.7189583333333 0.0850381944444442 -0.155996527777777 59 15.305 15.6915277777778 15.6947083333333 -0.00318055555555515 -0.386527777777777 60 15.579 15.7488715277778 15.6984166666667 0.0504548611111117 -0.169871527777778 61 16.348 15.7980069444444 15.6729166666667 0.125090277777777 0.549993055555555 62 15.928 15.6928298611111 15.720625 -0.0277951388888898 0.23517013888889 63 16.171 15.9861006944444 15.8614166666667 0.124684027777778 0.184899305555554 64 15.937 16.2327048611111 16.0333333333333 0.199371527777779 -0.29570486111111 65 15.713 16.0067256944444 16.2203333333333 -0.213607638888889 -0.293725694444444 66 15.594 16.4225069444444 16.4809583333333 -0.0584513888888892 -0.828506944444445 67 15.683 NA NA -0.0455451388888889 NA 68 16.438 NA NA -0.0727013888888889 NA 69 17.032 NA NA -0.163357638888888 NA 70 17.696 NA NA 0.0850381944444442 NA 71 17.745 NA NA -0.00318055555555515 NA 72 19.394 NA NA 0.0504548611111117 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/19dse1211211668.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/19dse1211211668.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/2clhw1211211668.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/2clhw1211211668.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/3b9e51211211668.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/3b9e51211211668.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/4j6dv1211211668.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/19/t121121179370dfwy6fkc1o6sj/4j6dv1211211668.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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