Roze Zalm Classical Decomposition

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

Title produced by software: Classical Decomposition

Date of computation: Sat, 31 May 2008 07:59:54 -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/31/t1212242619fveb4zlsb0j94te.htm/, Retrieved Sat, 31 May 2008 14:03:39 +0000

User-defined keywords:

Dataseries X:

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11.98 11.79 11.66 11.96 11.83 12.36 12.53 12.55 12.53 12.24 12.34 12.05 12.22 12.23 11.92 12.13 12.1 12.15 12.23 12.08 12.02 11.93 12.16 11.87 11.93 11.79 11.43 11.63 11.93 11.89 11.83 11.59 12.04 11.81 11.9 11.72 11.91 11.94 11.91 11.84 12.01 11.89 11.8 11.7 11.5 11.76 11.61 11.27 11.64 11.39 11.54 11.62 11.59 11.44 11.31 11.56 11.4 11.51 11.5 11.24 11.8 11.87 11.86 12.11 11.92 12.61 13.34 13.31 13.47 13.24 13.18 13.3

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 11.98 NA NA 1.00508696868977 NA 2 11.79 NA NA 0.999482778696822 NA 3 11.66 NA NA 0.989960964639692 NA 4 11.96 NA NA 1.00040810180015 NA 5 11.83 NA NA 1.01048064257572 NA 6 12.36 NA NA 1.00631505396788 NA 7 12.53 12.1985694611083 12.1616666666667 1.00303435338700 1.02716962345039 8 12.55 12.1754747754353 12.19 0.998808431126771 1.03076062588707 9 12.53 12.2153685778429 12.2191666666667 0.999689169570452 1.02575701421959 10 12.24 12.2487880992934 12.2370833333333 1.00095649965283 0.999282533159843 11 12.34 12.3094940908289 12.2554166666667 1.00441253248527 1.00247824231817 12 12.05 12.0294843023955 12.2579166666667 0.981364503407634 1.00170545113064 13 12.22 12.2989142068671 12.2366666666667 1.00508696868977 0.993583644414473 14 12.23 12.1982708628369 12.2045833333333 0.999482778696822 1.00260111761084 15 11.92 12.0416376836361 12.16375 0.989960964639692 0.989898576353833 16 12.13 12.1345334381267 12.1295833333333 1.00040810180015 0.99962640194204 17 12.1 12.2360785143898 12.1091666666667 1.01048064257572 0.988878911308902 18 12.15 12.1705419818632 12.0941666666667 1.00631505396788 0.998312155539675 19 12.23 12.1112218861675 12.0745833333333 1.00303435338700 1.00980727749429 20 12.08 12.0298152125627 12.0441666666667 0.998808431126771 1.00417170060808 21 12.02 12.0016850178473 12.0054166666667 0.999689169570452 1.00152603422982 22 11.93 11.9756103879298 11.9641666666667 1.00095649965283 0.996191393469536 23 12.16 11.9889190908773 11.93625 1.00441253248527 1.01426991940023 24 11.87 11.6962292731133 11.9183333333333 0.981364503407634 1.01485698705361 25 11.93 11.9513216301953 11.8908333333333 1.00508696868977 0.998215960472405 26 11.79 11.8476189879775 11.85375 0.999482778696822 0.995136660958128 27 11.43 11.7153630490402 11.8341666666667 0.989960964639692 0.975641979864755 28 11.63 11.8348278442958 11.83 1.00040810180015 0.982692790550856 29 11.93 11.9379867248299 11.8141666666667 1.01048064257572 0.999330982265769 30 11.89 11.8715825512470 11.7970833333333 1.00631505396788 1.00155138951977 31 11.83 11.8257750264328 11.79 1.00303435338700 1.00035726821775 32 11.59 11.7813616153199 11.7954166666667 0.998808431126771 0.98375725815333 33 12.04 11.8179921329387 11.8216666666667 0.999689169570452 1.01878558257308 34 11.81 11.8617515860943 11.8504166666667 1.00095649965283 0.995637104206859 35 11.9 11.9148436666066 11.8625 1.00441253248527 0.99875418704417 36 11.72 11.6447076366844 11.8658333333333 0.981364503407634 1.00646580108876 37 11.91 11.9249380972672 11.8645833333333 1.00508696868977 0.998747322866977 38 11.94 11.8617783273423 11.8679166666667 0.999482778696822 1.00659443048918 39 11.91 11.7310374309804 11.85 0.989960964639692 1.01525547677028 40 11.84 11.8302426404959 11.8254166666667 1.00040810180015 1.00082478101258 41 12.01 11.9350394896224 11.81125 1.01048064257572 1.00628070903685 42 11.89 11.8548106336808 11.7804166666667 1.00631505396788 1.00296836173993 43 11.8 11.7860715832779 11.7504166666667 1.00303435338700 1.00118176922851 44 11.7 11.7022892811890 11.71625 0.998808431126771 0.999804373218434 45 11.5 11.6742868148129 11.6779166666667 0.999689169570452 0.985070881195775 46 11.76 11.6644797426210 11.6533333333333 1.00095649965283 1.00818898566303 47 11.61 11.6779697110288 11.6266666666667 1.00441253248527 0.994179663699197 48 11.27 11.3744234963709 11.5904166666667 0.981364503407634 0.990819447121499 49 11.64 11.6100108470777 11.55125 1.00508696868977 1.00258304262738 50 11.39 11.5190390244809 11.525 0.999482778696822 0.98879776132309 51 11.54 11.3994005078261 11.515 0.989960964639692 1.01233393739236 52 11.62 11.5051100074108 11.5004166666667 1.00040810180015 1.00998599687575 53 11.59 11.6057912135832 11.4854166666667 1.01048064257572 0.998639367769715 54 11.44 11.5520775216121 11.4795833333333 1.00631505396788 0.990298063581856 55 11.31 11.5198495486497 11.485 1.00303435338700 0.98178365544068 56 11.56 11.4979497229877 11.5116666666667 0.998808431126771 1.00539663840139 57 11.4 11.5414114626909 11.545 0.999689169570452 0.987747472382559 58 11.51 11.5898250703552 11.57875 1.00095649965283 0.993112487041809 59 11.5 11.6641590387071 11.6129166666667 1.00441253248527 0.985926200237638 60 11.24 11.4578394791605 11.6754166666667 0.981364503407634 0.980987735117362 61 11.8 11.8688207415153 11.80875 1.00508696868977 0.994201551863144 62 11.87 11.9600608005808 11.96625 0.999482778696822 0.992469871007974 63 11.86 12.0036891799915 12.1254166666667 0.989960964639692 0.988029581752996 64 12.11 12.2887630204876 12.28375 1.00040810180015 0.985453131434826 65 11.92 12.5560640512054 12.4258333333333 1.01048064257572 0.949342082948012 66 12.61 12.6611205706726 12.5816666666667 1.00631505396788 0.995962397610287 67 13.34 NA NA 1.00303435338700 NA 68 13.31 NA NA 0.998808431126771 NA 69 13.47 NA NA 0.999689169570452 NA 70 13.24 NA NA 1.00095649965283 NA 71 13.18 NA NA 1.00441253248527 NA 72 13.3 NA NA 0.981364503407634 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/17qr81212242389.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/17qr81212242389.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/2y1mh1212242389.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/2y1mh1212242389.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/3z3dt1212242389.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/3z3dt1212242389.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/4sqzd1212242389.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212242619fveb4zlsb0j94te/4sqzd1212242389.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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