decompositie roomijs - Sophie Volckaerts - 2mar03

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 28 May 2008 05:57:52 -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/28/t121197592508kx37ybtp9yvov.htm/, Retrieved Wed, 28 May 2008 13:58:45 +0200

User-defined keywords:

Dataseries X:

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2,6900 2,7200 2,6800 2,7200 2,7000 2,7200 2,7200 2,7100 2,6800 2,6500 2,6600 2,6900 2,6700 2,6700 2,6500 2,6600 2,7600 2,7900 2,7900 2,7800 2,8100 2,8100 2,7900 2,7900 2,7900 2,8000 2,8000 2,8000 2,7700 2,7800 2,7500 2,7400 2,7400 2,7200 2,7100 2,7100 2,7000 2,6900 2,7000 2,7100 2,7600 2,7600 2,7500 2,7400 2,7100 2,7300 2,7300 2,7300 2,7200 2,7200 2,7500 2,8200 2,8500 2,8300 2,8500 2,8500 2,7900 2,8100 2,8000 2,7900 2,7900 2,8000 2,8000 2,8600 2,8600 2,8500 2,8100 2,7900 2,7800 2,7700 2,7800 2,8500 2,8200

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 3 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 2.69 NA NA -0.0225347222222223 NA 2 2.72 NA NA -0.0253472222222223 NA 3 2.68 NA NA -0.0229513888888891 NA 4 2.72 NA NA -0.00326388888888887 NA 5 2.7 NA NA 0.0311111111111110 NA 6 2.72 NA NA 0.033611111111111 NA 7 2.72 2.72048611111111 2.69416666666667 0.0263194444444444 -0.000486111111110521 8 2.71 2.70746527777778 2.69125 0.0162152777777777 0.00253472222222273 9 2.68 2.68621527777778 2.68791666666667 -0.00170138888888885 -0.00621527777777775 10 2.65 2.68381944444444 2.68416666666667 -0.000347222222221971 -0.0338194444444446 11 2.66 2.67069444444444 2.68416666666667 -0.0134722222222219 -0.0106944444444439 12 2.69 2.67194444444444 2.68958333333333 -0.0176388888888888 0.0180555555555557 13 2.67 2.67288194444444 2.69541666666667 -0.0225347222222223 -0.00288194444444434 14 2.67 2.67590277777778 2.70125 -0.0253472222222223 -0.00590277777777715 15 2.65 2.68663194444444 2.70958333333333 -0.0229513888888891 -0.0366319444444443 16 2.66 2.71840277777778 2.72166666666667 -0.00326388888888887 -0.0584027777777774 17 2.76 2.76486111111111 2.73375 0.0311111111111110 -0.00486111111111143 18 2.79 2.77694444444444 2.74333333333333 0.033611111111111 0.0130555555555554 19 2.79 2.77881944444444 2.7525 0.0263194444444444 0.0111805555555557 20 2.78 2.77913194444444 2.76291666666667 0.0162152777777777 0.000868055555555802 21 2.81 2.77288194444444 2.77458333333333 -0.00170138888888885 0.0371180555555557 22 2.81 2.78631944444444 2.78666666666667 -0.000347222222221971 0.0236805555555559 23 2.79 2.77944444444444 2.79291666666667 -0.0134722222222219 0.0105555555555563 24 2.79 2.77527777777778 2.79291666666667 -0.0176388888888888 0.0147222222222227 25 2.79 2.76829861111111 2.79083333333333 -0.0225347222222223 0.0217013888888893 26 2.8 2.76215277777778 2.7875 -0.0253472222222223 0.0378472222222221 27 2.8 2.75996527777778 2.78291666666667 -0.0229513888888891 0.0400347222222219 28 2.8 2.77298611111111 2.77625 -0.00326388888888887 0.0270138888888884 29 2.77 2.80027777777778 2.76916666666667 0.0311111111111110 -0.0302777777777776 30 2.78 2.79611111111111 2.7625 0.033611111111111 -0.0161111111111114 31 2.75 2.78173611111111 2.75541666666667 0.0263194444444444 -0.0317361111111114 32 2.74 2.76329861111111 2.74708333333333 0.0162152777777777 -0.0232986111111111 33 2.74 2.73663194444444 2.73833333333333 -0.00170138888888885 0.00336805555555575 34 2.72 2.73006944444444 2.73041666666667 -0.000347222222221971 -0.0100694444444440 35 2.71 2.71277777777778 2.72625 -0.0134722222222219 -0.00277777777777732 36 2.71 2.70736111111111 2.725 -0.0176388888888888 0.00263888888888886 37 2.7 2.70163194444444 2.72416666666667 -0.0225347222222223 -0.00163194444444459 38 2.69 2.69881944444444 2.72416666666667 -0.0253472222222223 -0.00881944444444471 39 2.7 2.69996527777778 2.72291666666667 -0.0229513888888891 3.47222222227828e-05 40 2.71 2.71881944444444 2.72208333333333 -0.00326388888888887 -0.00881944444444427 41 2.76 2.75444444444444 2.72333333333333 0.0311111111111110 0.00555555555555554 42 2.76 2.75861111111111 2.725 0.033611111111111 0.00138888888888911 43 2.75 2.75298611111111 2.72666666666667 0.0263194444444444 -0.00298611111111091 44 2.74 2.74496527777778 2.72875 0.0162152777777777 -0.00496527777777755 45 2.71 2.73038194444444 2.73208333333333 -0.00170138888888885 -0.0203819444444449 46 2.73 2.73840277777778 2.73875 -0.000347222222221971 -0.00840277777777798 47 2.73 2.73361111111111 2.74708333333333 -0.0134722222222219 -0.00361111111111123 48 2.73 2.73611111111111 2.75375 -0.0176388888888888 -0.00611111111111118 49 2.72 2.73829861111111 2.76083333333333 -0.0225347222222223 -0.0182986111111112 50 2.72 2.74423611111111 2.76958333333333 -0.0253472222222223 -0.0242361111111107 51 2.75 2.75454861111111 2.7775 -0.0229513888888891 -0.00454861111111127 52 2.82 2.78090277777778 2.78416666666667 -0.00326388888888887 0.0390972222222219 53 2.85 2.82152777777778 2.79041666666667 0.0311111111111110 0.0284722222222222 54 2.83 2.82944444444444 2.79583333333333 0.033611111111111 0.000555555555556086 55 2.85 2.82756944444444 2.80125 0.0263194444444444 0.0224305555555562 56 2.85 2.82371527777778 2.8075 0.0162152777777777 0.0262847222222229 57 2.79 2.81121527777778 2.81291666666667 -0.00170138888888885 -0.0212152777777774 58 2.81 2.81631944444444 2.81666666666667 -0.000347222222221971 -0.00631944444444432 59 2.8 2.80527777777778 2.81875 -0.0134722222222219 -0.00527777777777771 60 2.79 2.80236111111111 2.82 -0.0176388888888888 -0.0123611111111104 61 2.79 2.79663194444444 2.81916666666667 -0.0225347222222223 -0.00663194444444404 62 2.8 2.78965277777778 2.815 -0.0253472222222223 0.0103472222222223 63 2.8 2.78913194444444 2.81208333333333 -0.0229513888888891 0.0108680555555556 64 2.86 2.80673611111111 2.81 -0.00326388888888887 0.0532638888888886 65 2.86 2.83861111111111 2.8075 0.0311111111111110 0.0213888888888891 66 2.85 2.84277777777778 2.80916666666667 0.033611111111111 0.0072222222222229 67 2.81 2.83923611111111 2.81291666666667 0.0263194444444444 -0.029236111111111 68 2.79 NA NA 0.0162152777777777 NA 69 2.78 NA NA -0.00170138888888885 NA 70 2.77 NA NA -0.000347222222221971 NA 71 2.78 NA NA -0.0134722222222219 NA 72 2.85 NA NA -0.0176388888888888 NA 73 2.82 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/1sfih1211975867.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/1sfih1211975867.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/253z61211975867.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/253z61211975867.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/3ygk71211975867.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/3ygk71211975867.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/45cny1211975867.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/28/t121197592508kx37ybtp9yvov/45cny1211975867.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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