Koers € t.o.v. £

*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 11:55:03 -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/t124439735036qqinwg0oabv6q.htm/, Retrieved Sun, 07 Jun 2009 19:55:54 +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/t124439735036qqinwg0oabv6q.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:

Wesley De Bondt

IsPrivate?

No (this computation is public)

User-defined keywords:

Wesley De Bondt

Dataseries X:

» Textbox « » Textfile « » CSV «

0,63709 0,64218 0,65711 0,66977 0,68255 0,68902 0,71322 0,70224 0,70045 0,69919 0,69693 0,69763 0,69278 0,70196 0,69215 0,6769 0,67124 0,66533 0,67157 0,66428 0,66576 0,66942 0,68130 0,69144 0,69862 0,695 0,69867 0,68968 0,69233 0,68293 0,68399 0,66895 0,68756 0,68527 0,6776 0,68137 0,67933 0,67922 0,68598 0,68297 0,68935 0,69463 0,6833 0,68666 0,68782 0,67669 0,67511 0,67254 0,67397 0,67286 0,66341 0,668 0,68021 0,67934 0,68136 0,67562 0,6744 0,67766 0,68887 0,69614 0,70896 0,72064 0,74725 0,75094 0,77494 0,79487 0,79209 0,79152 0,79308 0,79279 0,79924 0,78668

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 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 0.63709 NA NA -0.000334777777777821 NA 2 0.64218 NA NA 0.00146797222222217 NA 3 0.65711 NA NA 0.00350805555555562 NA 4 0.66977 NA NA -0.00183786111111109 NA 5 0.68255 NA NA 0.00444555555555557 NA 6 0.68902 NA NA 0.00465688888888900 NA 7 0.71322 0.688946305555556 0.684602083333333 0.00434422222222226 0.0242736944444443 8 0.70224 0.685366805555556 0.689413333333333 -0.00404652777777781 0.0168731944444444 9 0.70045 0.691560638888889 0.693364166666667 -0.00180352777777777 0.00888936111111116 10 0.69919 0.690338138888889 0.69512125 -0.0047831111111111 0.00885186111111103 11 0.69693 0.691033638888889 0.694947083333333 -0.00391344444444448 0.00589636111111125 12 0.69763 0.691785305555556 0.69348875 -0.00170344444444453 0.00584469444444435 13 0.69278 0.690431472222222 0.69076625 -0.000334777777777821 0.00234852777777772 14 0.70196 0.688917138888889 0.687449166666667 0.00146797222222217 0.0130428611111112 15 0.69215 0.687930138888889 0.684422083333333 0.00350805555555562 0.00421986111111106 16 0.6769 0.679898388888889 0.68173625 -0.00183786111111109 -0.00299838888888881 17 0.67124 0.684290138888889 0.679844583333333 0.00444555555555557 -0.0130501388888890 18 0.66533 0.683592305555556 0.678935416666667 0.00465688888888900 -0.0182623055555556 19 0.67157 0.683265055555556 0.678920833333333 0.00434422222222226 -0.0116950555555555 20 0.66428 0.674827638888889 0.678874166666667 -0.00404652777777781 -0.0105476388888889 21 0.66576 0.677052305555555 0.678855833333333 -0.00180352777777777 -0.0112923055555554 22 0.66942 0.674876888888889 0.67966 -0.0047831111111111 -0.00545688888888884 23 0.6813 0.677157805555555 0.68107125 -0.00391344444444448 0.00414219444444452 24 0.69144 0.680979888888889 0.682683333333333 -0.00170344444444453 0.0104601111111111 25 0.69862 0.683599388888889 0.683934166666667 -0.000334777777777821 0.0150206111111113 26 0.695 0.686114222222222 0.68464625 0.00146797222222217 0.00888577777777777 27 0.69867 0.689257222222222 0.685749166666667 0.00350805555555562 0.00941277777777771 28 0.68968 0.685480055555556 0.687317916666667 -0.00183786111111109 0.00419994444444438 29 0.69233 0.692269722222222 0.687824166666667 0.00444555555555557 6.02777777777286e-05 30 0.68293 0.691907305555556 0.687250416666667 0.00465688888888900 -0.00897730555555565 31 0.68399 0.690371305555555 0.686027083333333 0.00434422222222226 -0.0063813055555555 32 0.66895 0.680519305555556 0.684565833333333 -0.00404652777777781 -0.0115693055555555 33 0.68756 0.681576055555556 0.683379583333333 -0.00180352777777777 0.00598394444444428 34 0.68527 0.677788138888889 0.68257125 -0.0047831111111111 0.00748186111111104 35 0.6776 0.678254055555556 0.6821675 -0.00391344444444448 -0.000654055555555533 36 0.68137 0.680827388888889 0.682530833333333 -0.00170344444444453 0.000542611111111091 37 0.67933 0.682654805555556 0.682989583333333 -0.000334777777777821 -0.00332480555555559 38 0.67922 0.685166722222222 0.68369875 0.00146797222222217 -0.00594672222222214 39 0.68598 0.687955555555556 0.6844475 0.00350805555555562 -0.00197555555555551 40 0.68297 0.682262972222222 0.684100833333333 -0.00183786111111109 0.000707027777777647 41 0.68935 0.688085138888889 0.683639583333333 0.00444555555555557 0.00126486111111113 42 0.69463 0.687824805555556 0.683167916666667 0.00465688888888900 0.00680519444444427 43 0.6833 0.686920888888889 0.682576666666667 0.00434422222222226 -0.00362088888888901 44 0.68666 0.678041805555556 0.682088333333333 -0.00404652777777781 0.00861819444444445 45 0.68782 0.679079388888889 0.680882916666667 -0.00180352777777777 0.00874061111111113 46 0.67669 0.674535638888889 0.67931875 -0.0047831111111111 0.00215436111111111 47 0.67511 0.674400722222222 0.678314166666667 -0.00391344444444448 0.00070927777777785 48 0.67254 0.675592805555556 0.67729625 -0.00170344444444453 -0.00305280555555554 49 0.67397 0.676243555555556 0.676578333333333 -0.000334777777777821 -0.00227355555555564 50 0.67286 0.677505472222222 0.6760375 0.00146797222222217 -0.00464547222222234 51 0.66341 0.678526388888889 0.675018333333333 0.00350805555555562 -0.0151163888888889 52 0.668 0.672661722222222 0.674499583333333 -0.00183786111111109 -0.00466172222222228 53 0.68021 0.679558888888889 0.675113333333333 0.00444555555555557 0.000651111111111047 54 0.67934 0.681326888888889 0.67667 0.00465688888888900 -0.00198688888888887 55 0.68136 0.683455472222222 0.67911125 0.00434422222222226 -0.00209547222222228 56 0.67562 0.678513472222222 0.68256 -0.00404652777777781 -0.00289347222222225 57 0.6744 0.686240638888889 0.688044166666667 -0.00180352777777777 -0.0118406388888888 58 0.67766 0.690210222222222 0.694993333333333 -0.0047831111111111 -0.0125502222222222 59 0.68887 0.698482805555556 0.70239625 -0.00391344444444448 -0.00961280555555566 60 0.69614 0.709453638888889 0.711157083333333 -0.00170344444444453 -0.0133136388888890 61 0.70896 0.720249805555556 0.720584583333334 -0.000334777777777821 -0.0112898055555557 62 0.72064 0.731495472222222 0.7300275 0.00146797222222217 -0.0108554722222223 63 0.74725 0.743309722222222 0.739801666666667 0.00350805555555562 0.00394027777777761 64 0.75094 0.747705888888889 0.74954375 -0.00183786111111109 0.00323411111111116 65 0.77494 0.763385138888889 0.758939583333333 0.00444555555555557 0.0115548611111111 66 0.79487 0.771967722222222 0.767310833333333 0.00465688888888900 0.0229022777777779 67 0.79209 NA NA 0.00434422222222226 NA 68 0.79152 NA NA -0.00404652777777781 NA 69 0.79308 NA NA -0.00180352777777777 NA 70 0.79279 NA NA -0.0047831111111111 NA 71 0.79924 NA NA -0.00391344444444448 NA 72 0.78668 NA NA -0.00170344444444453 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/1y4yk1244397301.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/1y4yk1244397301.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/2vy6f1244397301.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/2vy6f1244397301.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/3bt021244397301.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/3bt021244397301.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/4s1go1244397301.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/07/t124439735036qqinwg0oabv6q/4s1go1244397301.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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