*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 02 Jun 2010 12:20:40 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2.htm/, Retrieved Wed, 02 Jun 2010 14:21:31 +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/2010/Jun/02/t1275481291zub0hotqiftu3f2.htm/}, year = {2010}, } @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 = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

306 303 344 254 309 310 379 294 356 318 405 545 268 243 273 273 236 222 302 285 309 322 362 471 198 253 173 186 185 105 228 214 189 270 277 378 185 182 258 179 197 168 250 211 260 234 305 347 203 217 227 242 185 175 252 319 202 254 336 431 150 280 187 279 193 227 225 205 259 254 275 394 159 230 188 195 189 220 274

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 306 NA NA 0.773736976398098 NA 2 303 NA NA 0.91790475263952 NA 3 344 NA NA 0.87772387028514 NA 4 254 NA NA 0.909893385186033 NA 5 309 NA NA 0.790146803304475 NA 6 310 NA NA 0.711898353475538 NA 7 379 346.785703183131 342 1.01399328416120 1.09289395877966 8 294 336.862568840931 337.916666666667 0.99688059829622 0.872759478773758 9 356 328.149381087313 332.458333333333 0.987039120954446 1.08487177035167 10 318 360.042198137483 330.291666666667 1.09007351523901 0.883229803742534 11 405 417.510001755997 328.041666666667 1.27273466812447 0.970036641748985 12 545 532.762527915388 321.333333333333 1.65797467193585 1.02296984386739 13 268 243.308040036519 314.458333333333 0.773736976398098 1.10148435686620 14 243 285.353639976811 310.875 0.91790475263952 0.851574909013767 15 273 270.814385810894 308.541666666667 0.87772387028514 1.00807052469743 16 273 279.109795905816 306.75 0.909893385186033 0.978109704512566 17 236 241.093543358278 305.125 0.790146803304475 0.978873165629705 18 222 213.74748063103 300.25 0.711898353475538 1.03860873281223 19 302 298.367523864434 294.25 1.01399328416120 1.01217450240066 20 285 290.839914552922 291.75 0.99688059829622 0.979920518949749 21 309 284.267266834880 288 0.987039120954446 1.08700520971163 22 322 305.44768291593 280.208333333333 1.09007351523901 1.05419035078628 23 362 349.312635788994 274.458333333333 1.27273466812447 1.03632094264884 24 471 443.439142464843 267.458333333333 1.65797467193585 1.06215251405629 25 198 200.784745375306 259.5 0.773736976398098 0.986130692498072 26 253 232.650608762758 253.458333333333 0.91790475263952 1.08746760365451 27 173 215.481210155002 245.5 0.87772387028514 0.802854225087914 28 186 216.857923469338 238.333333333333 0.909893385186033 0.857704422436282 29 185 183.807900118704 232.625 0.790146803304475 1.00648557477957 30 105 160.32544168897 225.208333333333 0.711898353475538 0.654917890098186 31 228 223.881267198759 220.791666666667 1.01399328416120 1.01839695144116 32 214 216.613846671449 217.291666666667 0.99688059829622 0.987933150573638 33 189 215.05114847795 217.875 0.987039120954446 0.878860686574659 34 270 241.042506057225 221.125 1.09007351523901 1.12013438798176 35 277 281.698606544882 221.333333333333 1.27273466812447 0.983320448040153 36 378 372.146231571602 224.458333333333 1.65797467193585 1.01572975333830 37 185 176.412030618766 228 0.773736976398098 1.04868131357658 38 182 210.008958197650 228.791666666667 0.91790475263952 0.866629697904174 39 258 203.302791454796 231.625 0.87772387028514 1.26904307685006 40 179 212.080983197111 233.083333333333 0.909893385186033 0.844017211263278 41 197 183.906668469117 232.75 0.790146803304475 1.07119552346783 42 168 165.605354477247 232.625 0.711898353475538 1.01445995227819 43 250 235.330941365746 232.083333333333 1.01399328416120 1.06233374391452 44 211 233.560816842485 234.291666666667 0.99688059829622 0.903404958299575 45 260 231.419547233778 234.458333333333 0.987039120954446 1.12350059927025 46 234 257.030250947397 235.791666666667 1.09007351523901 0.910398675399066 47 305 302.804789791279 237.916666666667 1.27273466812447 1.007249588787 48 347 394.114395974752 237.708333333333 1.65797467193585 0.880455024084504 49 203 184.213878464114 238.083333333333 0.773736976398098 1.10197994685588 50 217 222.744886640524 242.666666666667 0.91790475263952 0.974208671062358 51 227 214.822917252288 244.75 0.87772387028514 1.05668428165609 52 242 221.255741497737 243.166666666667 0.909893385186033 1.09375692744441 53 185 193.816426293893 245.291666666667 0.790146803304475 0.95451145982578 54 175 178.033913231674 250.083333333333 0.711898353475538 0.982958790397838 55 252 254.892561806022 251.375 1.01399328416120 0.98865183909045 56 319 251.006227312669 251.791666666667 0.99688059829622 1.27088480399585 57 202 249.474137821236 252.75 0.987039120954446 0.8097031690906 58 254 275.379821787254 252.625 1.09007351523901 0.922362424201977 59 336 323.910973037677 254.5 1.27273466812447 1.03732206676715 60 431 426.099490687514 257 1.65797467193585 1.01150085700543 61 150 199.656378951393 258.041666666667 0.773736976398098 0.751290796656782 62 280 231.464981790599 252.166666666667 0.91790475263952 1.20968622481870 63 187 219.248108431642 249.791666666667 0.87772387028514 0.852914998162018 64 279 229.444781964411 252.166666666667 0.909893385186033 1.21597884079698 65 193 197.240395774880 249.625 0.790146803304475 0.978501382750624 66 227 174.800708209639 245.541666666667 0.711898353475538 1.29862174086708 67 225 247.794608816894 244.375 1.01399328416120 0.908010069606729 68 205 241.909691853216 242.666666666667 0.99688059829622 0.847423674634699 69 259 237.506288479664 240.625 0.987039120954446 1.09049744180637 70 254 258.529102030851 237.166666666667 1.09007351523901 0.982481268084432 71 275 297.183545007063 233.5 1.27273466812447 0.92535406021038 72 394 386.377180839051 233.041666666667 1.65797467193585 1.01972895796899 73 159 NA 234.791666666667 NA NA 74 230 NA NA NA NA 75 188 NA NA NA NA 76 195 NA NA NA NA 77 189 NA NA NA NA 78 220 NA NA NA NA 79 274 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/12pcl1275481236.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/12pcl1275481236.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/2dhto1275481236.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/2dhto1275481236.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/3o8a91275481236.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/3o8a91275481236.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/4o8a91275481236.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/02/t1275481291zub0hotqiftu3f2/4o8a91275481236.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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