*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 15 Jan 2010 02:12:07 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi.htm/, Retrieved Fri, 15 Jan 2010 10:13:13 +0100

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/Jan/15/t1263546788h5nt58zft9xkqvi.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

104.0 99.0 105.4 107.1 110.7 117.1 118.7 126.5 127.5 134.6 131.8 135.9 142.7 141.7 153.4 145.0 137.7 148.3 152.2 169.4 168.6 161.1 174.1 179.0 190.6 190.0 181.6 174.8 180.5 196.8 193.8 197.0 216.3 221.4 217.9 229.7 227.4 204.2 196.6 198.8 207.5 190.7 201.6 210.5 223.5 223.8 231.2 244.0 234.7 250.2 265.7 287.6 283.3 295.4 312.3 333.8 347.7 383.2 407.1 413.6 362.7 321.9 239.4 191.0 159.7 163.4 157.6 166.2 176.7 198.3 226.2 216.2 235.9

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 7 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 104 NA NA 1.07536671520055 NA 2 99 NA NA 1.02963575865129 NA 3 105.4 NA NA 0.974669573580213 NA 4 107.1 NA NA 0.928468928421948 NA 5 110.7 NA NA 0.89515699042328 NA 6 117.1 NA NA 0.912413213065011 NA 7 118.7 110.542129097104 119.804166666667 0.922690188269222 1.07379874957655 8 126.5 123.557401164046 123.195833333333 1.00293490308016 1.02381564202736 9 127.5 131.777042987223 126.975 1.03781880675112 0.967543337668931 10 134.6 136.297302959724 130.554166666667 1.04399044810052 0.987547053955827 11 131.8 143.656661600067 133.258333333333 1.07803135463749 0.917465285159725 12 135.9 149.091983640802 135.683333333333 1.09882311981920 0.911517820618815 13 142.7 148.808349910523 138.379166666667 1.07536671520055 0.958951564786548 14 141.7 145.757812084073 141.5625 1.02963575865129 0.972160585933242 15 153.4 141.388005017480 145.0625 0.974669573580213 1.08495766653639 16 145 137.301211410931 147.879166666667 0.928468928421948 1.05607225537164 17 137.7 134.941186485516 150.745833333333 0.89515699042328 1.02044456245225 18 148.3 140.789160497652 154.304166666667 0.912413213065011 1.05334813756825 19 152.2 145.873474222913 158.095833333333 0.922690188269222 1.04336995338453 20 169.4 162.579926684723 162.104166666667 1.00293490308016 1.04194904902684 21 168.6 171.542800265903 165.291666666667 1.03781880675112 0.98284509602652 22 161.1 175.085898066859 167.708333333333 1.04399044810052 0.920119791363677 23 174.1 184.055886615107 170.733333333333 1.07803135463749 0.945908349913704 24 179 191.785840275444 174.5375 1.09882311981920 0.933332720199359 25 190.6 191.728923930965 178.291666666667 1.07536671520055 0.994111874683179 26 190 186.544258573647 181.175 1.02963575865129 1.01852504844038 27 181.6 179.643785780503 184.3125 0.974669573580213 1.01088940656087 28 174.8 175.306539547669 188.8125 0.928468928421948 0.997110549617966 29 180.5 172.899572700256 193.15 0.89515699042328 1.04395862396329 30 196.8 179.825239129950 197.0875 0.912413213065011 1.09439587541870 31 193.8 185.214677125242 200.733333333333 0.922690188269222 1.04635336145069 32 197 203.453702880668 202.858333333333 1.00293490308016 0.968279255726038 33 216.3 211.792872987734 204.075 1.03781880675112 1.02128082474488 34 221.4 214.748835174278 205.7 1.04399044810052 1.03097183190924 35 217.9 224.041866277536 207.825 1.07803135463749 0.97258607786311 36 229.7 229.319806676602 208.695833333333 1.09882311981920 1.00165791751226 37 227.4 224.500724576701 208.766666666667 1.07536671520055 1.01291432546049 38 204.2 215.867426950237 209.654166666667 1.02963575865129 0.945950961128902 39 196.6 205.184189731528 210.516666666667 0.974669573580213 0.958163493284937 40 198.8 195.829571486329 210.916666666667 0.928468928421948 1.01516843697878 41 207.5 189.389110428012 211.570833333333 0.89515699042328 1.09562793515983 42 190.7 194.089299027533 212.720833333333 0.912413213065011 0.98253742455398 43 201.6 197.105846926561 213.620833333333 0.922690188269222 1.02280070907847 44 210.5 216.475141038992 215.841666666667 1.00293490308016 0.972398026811235 45 223.5 228.981746974549 220.6375 1.03781880675112 0.9760603321139 46 223.8 237.212029649241 227.216666666667 1.04399044810052 0.943459740768322 47 231.2 252.34018933677 234.075 1.07803135463749 0.916223454566102 48 244 265.471087318654 241.595833333333 1.09882311981920 0.919120806956725 49 234.7 269.455533966731 250.570833333333 1.07536671520055 0.87101569800744 50 250.2 268.035638721903 260.320833333333 1.02963575865129 0.93345795802771 51 265.7 263.778075596591 270.633333333333 0.974669573580213 1.00728614157587 52 287.6 262.246048832779 282.45 0.928468928421948 1.09668001207289 53 283.3 265.343181065427 296.420833333333 0.89515699042328 1.06767394158188 54 295.4 283.59323350749 310.816666666667 0.912413213065011 1.04163275105856 55 312.3 298.228847018417 323.216666666667 0.922690188269222 1.04718240077129 56 333.8 332.510530429937 331.5375 1.00293490308016 1.00387798115264 57 347.7 346.039059886019 333.429166666667 1.03781880675112 1.00479986309791 58 383.2 342.750764031803 328.308333333333 1.04399044810052 1.11801355449187 59 407.1 344.035739643311 319.133333333333 1.07803135463749 1.18330729366104 60 413.6 338.968618745560 308.483333333333 1.09882311981920 1.22017194845538 61 362.7 318.886557308783 296.5375 1.07536671520055 1.13739507573156 62 321.9 291.498463572169 283.108333333333 1.02963575865129 1.10429398513898 63 239.4 262.186115293077 269 0.974669573580213 0.913091830711148 64 191 235.989721261113 254.170833333333 0.928468928421948 0.809357284627943 65 159.7 213.879113757676 238.929166666667 0.89515699042328 0.746683475511964 66 163.4 203.620215382342 223.166666666667 0.912413213065011 0.802474350069715 67 157.6 193.449687055545 209.658333333333 0.922690188269222 0.814682113984236 68 166.2 NA NA 1.00293490308016 NA 69 176.7 NA NA 1.03781880675112 NA 70 198.3 NA NA 1.04399044810052 NA 71 226.2 NA NA 1.07803135463749 NA 72 216.2 NA NA 1.09882311981920 NA 73 235.9 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/1eo3e1263546719.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/1eo3e1263546719.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/2qrkh1263546719.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/2qrkh1263546719.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/3is7b1263546719.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/3is7b1263546719.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/4uwfr1263546719.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/15/t1263546788h5nt58zft9xkqvi/4uwfr1263546719.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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