Classical Decomposition Eigen Reeks

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 16 Dec 2010 16:07:33 +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/Dec/16/t1292515686ykluk2wqqnv2wq5.htm/, Retrieved Thu, 16 Dec 2010 17:08:11 +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/Dec/16/t1292515686ykluk2wqqnv2wq5.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:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

95,05 96,84 96,92 97,44 97,78 97,69 96,67 98,29 98,2 98,71 98,54 98,2 96,92 99,06 99,65 99,82 99,99 100,33 99,31 101,1 101,1 100,93 100,85 100,93 99,6 101,88 101,81 102,38 102,74 102,82 101,72 103,47 102,98 102,68 102,9 103,03 101,29 103,69 103,68 104,2 104,08 104,16 103,05 104,66 104,46 104,95 105,85 106,23 104,86 107,44 108,23 108,45 109,39 110,15 109,13 110,28 110,17 109,99 109,26 109,11 107,06 109,53 108,92 109,24 109,12 109 107,23 109,49 109,04 109,02 109,23 109,46

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 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 95.05 NA NA 0.98140733479096 NA 2 96.84 NA NA 1.00247656470811 NA 3 96.92 NA NA 1.00208045626739 NA 4 97.44 NA NA 1.00383742651187 NA 5 97.78 NA NA 1.00447763133924 NA 6 97.69 NA NA 1.00487913979828 NA 7 96.67 96.9027028458144 97.6054166666667 0.992800462875415 0.997598592825789 8 98.29 98.3910699561508 97.7758333333333 1.00629231786468 0.998972773075892 9 98.2 98.2328456813316 97.9820833333333 1.00255926736264 0.999665634431092 10 98.71 98.3270751126927 98.195 1.00134502889855 1.00389439924729 11 98.54 98.3626227943673 98.38625 0.999759852564431 1.00180329886082 12 98.2 98.3994890586527 98.5883333333333 0.998084517018437 0.997972661641223 13 96.92 96.9712230718033 98.8083333333333 0.98140733479096 0.999471770385268 14 99.06 99.2806842844362 99.0354166666667 1.00247656470811 0.997777167975556 15 99.65 99.4798671618514 99.2733333333333 1.00208045626739 1.00171022381717 16 99.82 99.868439438911 99.4866666666667 1.00383742651187 0.99951496749941 17 99.99 100.121726436085 99.6754166666666 1.00447763133924 0.998684337148645 18 100.33 100.372771578393 99.8854166666666 1.00487913979828 0.999573872697544 19 99.31 99.3900816721768 100.110833333333 0.992800462875415 0.99919426897705 20 101.1 100.971371174542 100.34 1.00629231786468 1.00127391382291 21 101.1 100.804827935145 100.5475 1.00255926736264 1.00292815404680 22 100.93 100.879670482193 100.744166666667 1.00134502889855 1.00049890644533 23 100.85 100.941170080773 100.965416666667 0.999759852564431 0.999096799841927 24 100.93 100.989934248864 101.18375 0.998084517018437 0.999406532449892 25 99.6 99.5028450758412 101.387916666667 0.98140733479096 1.00097640347957 26 101.88 101.838670318716 101.587083333333 1.00247656470811 1.00040583484794 27 101.81 101.975882565004 101.764166666667 1.00208045626739 0.998373315721016 28 102.38 102.306509588552 101.915416666667 1.00383742651187 1.00071833563420 29 102.74 102.530798621914 102.07375 1.00447763133924 1.00204037597383 30 102.82 102.745542447241 102.246666666667 1.00487913979828 1.00072467915381 31 101.72 101.667317733897 102.404583333333 0.992800462875415 1.00051818290555 32 103.47 103.195696485489 102.550416666667 1.00629231786468 1.00265809063607 33 102.98 102.966596355396 102.70375 1.00255926736264 1.00013017468848 34 102.68 102.995846309932 102.8575 1.00134502889855 0.99693340730478 35 102.9 102.964434082400 102.989166666667 0.999759852564431 0.999374210299173 36 103.03 102.903345441698 103.100833333333 0.998084517018437 1.00123081089111 37 101.29 101.293095622389 103.212083333333 0.98140733479096 0.999969438959586 38 103.69 103.572954775661 103.317083333333 1.00247656470811 1.00113007516868 39 103.68 103.643511457642 103.428333333333 1.00208045626739 1.00035205814474 40 104.2 103.982081559638 103.584583333333 1.00383742651187 1.00209573069796 41 104.08 104.266870794745 103.802083333333 1.00447763133924 0.99820776442871 42 104.16 104.566048488843 104.058333333333 1.00487913979828 0.996116822862576 43 103.05 103.589213963280 104.340416666667 0.992800462875415 0.994794690077758 44 104.66 105.303878891415 104.645416666667 1.00629231786468 0.993885515916472 45 104.46 105.259950679488 104.99125 1.00255926736264 0.992400236991147 46 104.95 105.499626109274 105.357916666667 1.00134502889855 0.994790255382473 47 105.85 105.730852907767 105.75625 0.999759852564431 1.00112689048614 48 106.23 106.023607163027 106.227083333333 0.998084517018437 1.00194666869479 49 104.86 104.745604842239 106.73 0.98140733479096 1.00109212370231 50 107.44 107.483031076592 107.2175 1.00247656470811 0.999599647719639 51 108.23 107.913626801912 107.689583333333 1.00208045626739 1.00293172611712 52 108.45 108.552469709427 108.1375 1.00383742651187 0.99905603520858 53 109.39 108.975359691648 108.489583333333 1.00447763133924 1.00380489965369 54 110.15 109.282281251629 108.751666666667 1.00487913979828 1.00794015954309 55 109.13 108.178847769781 108.963333333333 0.992800462875415 1.00879240489086 56 110.28 109.828840014080 109.142083333333 1.00629231786468 1.00410784622565 57 110.17 109.537536886902 109.257916666667 1.00255926736264 1.00577393951949 58 109.99 109.466621332094 109.319583333333 1.00134502889855 1.00478117129713 59 109.26 109.314991979211 109.34125 0.999759852564431 0.999496940188945 60 109.11 109.072755362519 109.282083333333 0.998084517018437 1.00034146599999 61 107.06 107.125517629107 109.155 0.98140733479096 0.999388403150275 62 109.53 109.312968505753 109.042916666667 1.00247656470811 1.00198541396519 63 108.92 109.189609249559 108.962916666667 1.00208045626739 0.99753081587697 64 109.24 109.293218077074 108.875416666667 1.00383742651187 0.999513070636855 65 109.12 109.321067409767 108.83375 1.00447763133924 0.998160762472125 66 109 109.378163469552 108.847083333333 1.00487913979828 0.996542605419985 67 107.23 NA NA 0.992800462875415 NA 68 109.49 NA NA 1.00629231786468 NA 69 109.04 NA NA 1.00255926736264 NA 70 109.02 NA NA 1.00134502889855 NA 71 109.23 NA NA 0.999759852564431 NA 72 109.46 NA NA 0.998084517018437 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/1q0m41292515649.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/1q0m41292515649.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/2q0m41292515649.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/2q0m41292515649.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/309lo1292515649.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/309lo1292515649.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/409lo1292515649.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/16/t1292515686ykluk2wqqnv2wq5/409lo1292515649.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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