Decompositie - Eigen reeks: Faxtoestellen - Kirsten Witvrouwen

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 21 May 2008 08:33:34 -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/21/t1211380751rwkftc3vrfw5tcm.htm/, Retrieved Wed, 21 May 2008 16:39:11 +0200

User-defined keywords:

Dataseries X:

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77.5 77.7 76.6 77 76.5 77.6 77.8 76.9 76.9 77 77 76.3 76.5 77.1 76.4 75.4 75.4 75.5 75.5 75.8 75.7 75.9 76.1 76 76 75.89 74.87 74.9 74.79 74.64 74.09 74.33 73.93 73.78 72.85 71.51 71.5 71.5 71.31 70.85 70.62 70.07 68.83 68.82 68.4 68.21 67.75 67.7 67.42 66.27 64.8 62.69 62.75 62.31 62.4 61.75 61.69 60.39 59.9 59.62 58.97 58.54 58.32 56.03 53.63 53.61 53.48 53.48 52.81 52.8 52.57 52.36

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 77.5 NA NA 0.308949652777776 NA 2 77.7 NA NA 0.462178819444438 NA 3 76.6 NA NA -0.0665711805555569 NA 4 77 NA NA -0.620112847222221 NA 5 76.5 NA NA -0.338967013888881 NA 6 77.6 NA NA -0.247092013888889 NA 7 77.8 76.7092621527778 77.025 -0.315737847222224 1.09073784722223 8 76.9 76.9885329861111 76.9583333333333 0.030199652777779 -0.0885329861111046 9 76.9 77.0918663194444 76.925 0.166866319444453 -0.191866319444443 10 77 77.0469704861111 76.85 0.196970486111112 -0.0469704861110927 11 77 76.9430121527778 76.7375 0.205512152777772 0.0569878472222314 12 76.3 76.8219704861111 76.6041666666667 0.217803819444442 -0.521970486111101 13 76.5 76.7297829861111 76.4208333333333 0.308949652777776 -0.22978298611109 14 77.1 76.7413454861111 76.2791666666667 0.462178819444438 0.358654513888908 15 76.4 76.1167621527778 76.1833333333333 -0.0665711805555569 0.283237847222225 16 75.4 75.4673871527778 76.0875 -0.620112847222221 -0.0673871527777692 17 75.4 75.6651996527778 76.0041666666667 -0.338967013888881 -0.265199652777781 18 75.5 75.7070746527778 75.9541666666667 -0.247092013888889 -0.207074652777763 19 75.5 75.6050954861111 75.9208333333333 -0.315737847222224 -0.105095486111097 20 75.8 75.8797829861111 75.8495833333333 0.030199652777779 -0.0797829861111126 21 75.7 75.9022829861111 75.7354166666667 0.166866319444453 -0.202282986111101 22 75.9 75.8478038194444 75.6508333333333 0.196970486111112 0.0521961805555691 23 76.1 75.8100954861111 75.6045833333333 0.205512152777772 0.289904513888885 24 76 75.7611371527778 75.5433333333333 0.217803819444442 0.238862847222222 25 76 75.7576996527778 75.44875 0.308949652777776 0.242300347222226 26 75.89 75.7909288194444 75.32875 0.462178819444438 0.0990711805555549 27 74.87 75.1271788194445 75.19375 -0.0665711805555569 -0.257178819444448 28 74.9 74.4115538194444 75.0316666666667 -0.620112847222221 0.488446180555556 29 74.79 74.4689496527778 74.8079166666667 -0.338967013888881 0.321050347222226 30 74.64 74.2383246527778 74.4854166666667 -0.247092013888889 0.401675347222223 31 74.09 73.7950954861111 74.1108333333333 -0.315737847222224 0.294904513888895 32 74.33 73.7706163194444 73.7404166666667 0.030199652777779 0.559383680555555 33 73.93 73.5760329861111 73.4091666666667 0.166866319444453 0.353967013888891 34 73.78 73.2890538194444 73.0920833333333 0.196970486111112 0.490946180555554 35 72.85 72.9550954861111 72.7495833333333 0.205512152777772 -0.105095486111111 36 71.51 72.6032204861111 72.3854166666667 0.217803819444442 -1.09322048611111 37 71.5 72.2847829861111 71.9758333333333 0.308949652777776 -0.784782986111111 38 71.5 71.9892621527778 71.5270833333333 0.462178819444438 -0.489262152777769 39 71.31 71.0005121527778 71.0670833333333 -0.0665711805555569 0.309487847222229 40 70.85 69.9844704861111 70.6045833333333 -0.620112847222221 0.865529513888873 41 70.62 69.8210329861111 70.16 -0.338967013888881 0.798967013888884 42 70.07 69.5416579861111 69.78875 -0.247092013888889 0.528342013888874 43 68.83 69.1442621527778 69.46 -0.315737847222224 -0.314262152777786 44 68.82 69.1022829861111 69.0720833333333 0.030199652777779 -0.282282986111113 45 68.4 68.7497829861111 68.5829166666666 0.166866319444453 -0.349782986111094 46 68.21 68.1686371527778 67.9716666666667 0.196970486111112 0.0413628472222172 47 67.75 67.5092621527778 67.30375 0.205512152777772 0.240737847222235 48 67.7 66.8703038194444 66.6525 0.217803819444442 0.829696180555558 49 67.42 66.3701996527778 66.06125 0.308949652777776 1.04980034722223 50 66.27 65.9609288194444 65.49875 0.462178819444438 0.309071180555563 51 64.8 64.8580121527778 64.9245833333333 -0.0665711805555569 -0.0580121527777777 52 62.69 63.6990538194444 64.3191666666667 -0.620112847222221 -1.00905381944444 53 62.75 63.3272829861111 63.66625 -0.338967013888881 -0.577282986111108 54 62.31 62.7554079861111 63.0025 -0.247092013888889 -0.445407986111107 55 62.4 61.9980121527778 62.31375 -0.315737847222224 0.401987847222216 56 61.75 61.6697829861111 61.6395833333333 0.030199652777779 0.0802170138888911 57 61.69 61.2143663194445 61.0475 0.166866319444453 0.475633680555539 58 60.39 60.6969704861111 60.5 0.196970486111112 -0.306970486111112 59 59.9 60.0480121527778 59.8425 0.205512152777772 -0.148012152777774 60 59.62 59.3178038194444 59.1 0.217803819444442 0.302196180555562 61 58.97 58.6747829861111 58.3658333333333 0.308949652777776 0.295217013888887 62 58.54 58.1117621527778 57.6495833333333 0.462178819444438 0.428237847222235 63 58.32 56.8684288194444 56.935 -0.0665711805555569 1.45157118055556 64 56.03 55.6286371527778 56.24875 -0.620112847222221 0.401362847222238 65 53.63 55.2881163194444 55.6270833333333 -0.338967013888881 -1.65811631944444 66 53.61 54.7720746527778 55.0191666666667 -0.247092013888889 -1.16207465277778 67 53.48 NA NA -0.315737847222224 NA 68 53.48 NA NA 0.030199652777779 NA 69 52.81 NA NA 0.166866319444453 NA 70 52.8 NA NA 0.196970486111112 NA 71 52.57 NA NA 0.205512152777772 NA 72 52.36 NA NA 0.217803819444442 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/1k0dp1211380409.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/1k0dp1211380409.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/2h6a91211380409.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/2h6a91211380409.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/3nc8v1211380409.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/3nc8v1211380409.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/4w37c1211380409.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/21/t1211380751rwkftc3vrfw5tcm/4w37c1211380409.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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