*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 30 May 2010 11:10:50 +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/May/30/t1275218008vq1ht1vka8wtv5s.htm/, Retrieved Sun, 30 May 2010 13:13:29 +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/May/30/t1275218008vq1ht1vka8wtv5s.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:

KDGP2W51

Dataseries X:

» Textbox « » Textfile « » CSV «

41086 39690 43129 37863 35953 29133 24693 22205 21725 27192 21790 13253 37702 30364 32609 30212 29965 28352 25814 22414 20506 28806 22228 13971 36845 35338 35022 34777 26887 23970 22780 17351 21382 24561 17409 11514 31514 27071 29462 26105 22397 23843 21705 18089 20764 25316 17704 15548 28029 29383 36438 32034 22679 24319 18004 17537 20366 22782 19169 13807 29743 25591 29096 26482 22405 27044 17970 18730 19684 19785 18479 10698

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 'RServer@AstonUniversity' @ vre.aston.ac.uk Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 41086 NA NA 1.32718577010684 NA 2 39690 NA NA 1.20084764006351 NA 3 43129 NA NA 1.32843407985928 NA 4 37863 NA NA 1.22345091771013 NA 5 35953 NA NA 1.01798223782367 NA 6 29133 NA NA 1.05339554978969 NA 7 24693 26076.9299732887 29668.3333333333 0.878948260433304 0.94692895311272 8 22205 22272.1981471665 29138.75 0.764349814153542 0.996982868654342 9 21725 23606.10620385 28311.8333333333 0.833789388554255 0.92031272808799 10 27192 28306.4131639731 27554.7083333333 1.02728044955317 0.960630364662682 11 21790 21346.1448649119 26986.4166666667 0.790995897253687 1.02079322228426 12 13253 14776.5987209382 26704.375 0.553339994698928 0.896891108047804 13 37702 35460.4682980066 26718.5416666667 1.32718577010684 1.06321212915621 14 30364 32151.4446797421 26773.9583333333 1.20084764006351 0.944405463034502 15 32609 35511.5337685382 26731.875 1.32843407985928 0.918265040663781 16 30212 32725.272963883 26748.3333333333 1.22345091771013 0.923200855599989 17 29965 27316.3657060541 26833.8333333333 1.01798223782367 1.09696144510757 18 28352 28317.3791694465 26882 1.05339554978969 1.0012226000982 19 25814 23622.7965616264 26876.2083333333 0.878948260433304 1.0927580031711 20 22414 20673.9426857715 27047.75 0.764349814153542 1.08416668947361 21 20506 22808.7603598205 27355.5416666667 0.833789388554255 0.899040529888816 22 28806 28400.4949318113 27646.2916666667 1.02728044955317 1.01427809864449 23 22228 21917.1120700795 27708.25 0.790995897253687 1.01418471233466 24 13971 15160.0863930976 27397.4166666667 0.553339994698928 0.921564669074773 25 36845 35951.3611347248 27088.4166666667 1.32718577010684 1.02485688544382 26 35338 32123.9252546573 26751.0416666667 1.20084764006351 1.100052366573 27 35022 35305.2390262201 26576.5833333333 1.32843407985928 0.99197742221743 28 34777 32343.4033461928 26436.2083333333 1.22345091771013 1.07524244210663 29 26887 26527.1325602547 26058.5416666667 1.01798223782367 1.01356601354963 30 23970 27130.5974081647 25755.375 1.05339554978969 0.883504319473128 31 22780 22352.4233425468 25430.875 0.878948260433304 1.01912887255671 32 17351 19005.0167144761 24864.2916666667 0.764349814153542 0.912969468044915 33 21382 20251.2156341038 24288.1666666667 0.833789388554255 1.05583785123456 34 24561 24341.5814655706 23695.1666666667 1.02728044955317 1.00901414457149 35 17409 18308.9842847568 23146.75 0.790995897253687 0.950844663430834 36 11514 12701.5737408172 22954.375 0.553339994698928 0.906501842602318 37 31514 30398.2499743766 22904.2916666667 1.32718577010684 1.0367044164241 38 27071 27487.7026929638 22890.25 1.20084764006351 0.984840395808325 39 29462 30414.8303668981 22895.25 1.32843407985928 0.968672178821844 40 26105 28018.198489358 22900.9583333333 1.22345091771013 0.931715863527603 41 22397 23357.3055353781 22944.7083333333 1.01798223782367 0.958886287892942 42 23843 24359.8598718491 23125.0833333333 1.05339554978969 0.978782313421826 43 21705 20345.8577096659 23147.9583333333 0.878948260433304 1.06680191662249 44 18089 17655.7800529505 23099.0833333333 0.764349814153542 1.02453700407177 45 20764 19582.4470620343 23486.0833333333 0.833789388554255 1.06033734876049 46 25316 24679.171503305 24023.7916666667 1.02728044955317 1.02580428992966 47 17704 19207.4237913874 24282.5833333333 0.790995897253687 0.921726942263774 48 15548 13454.0008544422 24314.1666666667 0.553339994698928 1.15564137153049 49 28029 32091.0754241478 24179.7916666667 1.32718577010684 0.873420402075675 50 29383 28823.4455512611 24002.5833333333 1.20084764006351 1.01941317000925 51 36438 31833.2658556679 23963 1.32843407985928 1.1446516409975 52 32034 29168.0894206408 23840.8333333333 1.22345091771013 1.0982549984001 53 22679 24224.2022427381 23796.2916666667 1.01798223782367 0.936212461105861 54 24319 25054.7936943416 23784.7916666667 1.05339554978969 0.970632618120188 55 18004 20904.6124433922 23783.6666666667 0.878948260433304 0.861245337542286 56 17537 18112.8612418143 23697.0833333333 0.764349814153542 0.968207052760668 57 20366 19371.5678291791 23233.1666666667 0.833789388554255 1.05133462503345 58 22782 23315.0714763545 22695.9166666667 1.02728044955317 0.97713618519698 59 19169 17760.3627136866 22453.1666666667 0.790995897253687 1.07931354269178 60 13807 12480.7449712661 22555.2916666667 0.553339994698928 1.10626409174991 61 29743 30083.8728450825 22667.4166666667 1.32718577010684 0.988669249905494 62 25591 27278.1047444544 22715.7083333333 1.20084764006351 0.938151687580225 63 29096 30204.6056737604 22737 1.32843407985928 0.963296800304747 64 26482 27630.0586857145 22583.7083333333 1.22345091771013 0.958448923370978 65 22405 22833.4264262381 22430.0833333333 1.01798223782367 0.981236875349299 66 27044 23461.0062275098 22271.7916666667 1.05339554978969 1.15272123189196 67 17970 NA NA 0.878948260433304 NA 68 18730 NA NA 0.764349814153542 NA 69 19684 NA NA 0.833789388554255 NA 70 19785 NA NA 1.02728044955317 NA 71 18479 NA NA 0.790995897253687 NA 72 10698 NA NA 0.553339994698928 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/1flax1275217846.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/1flax1275217846.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/2flax1275217846.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/2flax1275217846.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/3pur01275217846.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/3pur01275217846.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/4pur01275217846.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/30/t1275218008vq1ht1vka8wtv5s/4pur01275217846.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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