clasical demoposition niet werkende-werkzoekende/filiz Aydemir

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Thu, 04 Jun 2009 04:09:24 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf.htm/, Retrieved Thu, 04 Jun 2009 12:12:24 +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/2009/Jun/04/t1244110339ccw8mgdnkral3lf.htm/}, year = {2009}, } @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 = {2009}, 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 «

233084 233898 231355 232662 230037 231814 246796 247891 248291 245766 238776 242541 246861 246843 246947 241679 240085 241514 250525 250567 252145 251877 245817 248269 246310 246733 245028 240022 238614 238096 248530 248381 247567 241783 235000 237384 238020 236412 232279 230408 230254 229217 239658 239906 236558 223566 216054 214685 216086 211692 204681 203075 198401 191246 206750 209611 199573 195635 190062 193134 194795 190835 185045 184425 177293 180549 195344 196597 189102 185749 185145 192243 197356

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 233084 NA NA 1.00580857979764 NA 2 233898 NA NA 1.00060436132505 NA 3 231355 NA NA 0.987408024483121 NA 4 232662 NA NA 0.979843367845825 NA 5 230037 NA NA 0.969488120195432 NA 6 231814 NA NA 0.969646556612428 NA 7 246796 246193.945113887 239149.958333333 1.02945426722900 1.00244544960614 8 247891 248801.253923383 240263.375 1.03553549900555 0.996341441576241 9 248291 248136.779079519 241452.416666667 1.02768397394871 1.00062151576664 10 245766 245152.010210302 242477.791666667 1.01102871535267 1.00250452684100 11 238776 240750.66648037 243272.166666667 0.989635065034993 0.991797877408862 12 242541 242597.103506949 244095 0.993863469169582 0.999768737935704 13 246861 246075.637094793 244654.541666667 1.00580857979764 1.00319155083567 14 246843 245069.437698577 244921.416666667 1.00060436132505 1.00723697870317 15 246947 242106.029451102 245193.5 0.987408024483121 1.01999524984930 16 241679 240658.063945596 245608.708333333 0.979843367845825 1.00424226821103 17 240085 238646.004435579 246156.708333333 0.969488120195432 1.00602983304843 18 241514 239200.896992524 246688.75 0.969646556612428 1.00967012681206 19 250525 254176.848229114 246904.458333333 1.02945426722900 0.985632648077285 20 250567 255649.811093369 246876.916666667 1.03553549900555 0.980118072172123 21 252145 253624.568680239 246792.375 1.02768397394871 0.994166303809057 22 251877 249363.534576497 246643.375 1.01102871535267 1.01007952276491 23 245817 243957.950021766 246513.041666667 0.989635065034993 1.00762037055185 24 248269 244797.848515514 246309.333333333 0.993863469169582 1.01417966499925 25 246310 247513.189007469 246083.791666667 1.00580857979764 0.995138889316188 26 246733 246058.201574959 245909.583333333 1.00060436132505 1.00274243419127 27 245028 242534.811385734 245627.75 0.987408024483121 1.01027971448726 28 240022 240077.710884183 245016.416666667 0.979843367845825 0.999767946453765 29 238614 236695.798291129 244145.125 0.969488120195432 1.00810408010079 30 238096 235857.676871144 243240.875 0.969646556612428 1.00949014320224 31 248530 249582.865667677 242441.916666667 1.02945426722900 0.995781498602236 32 248381 250254.196523113 241666.458333333 1.03553549900555 0.992514824729663 33 247567 247368.885050151 240705.208333333 1.02768397394871 1.00080088872054 34 241783 242417.809428220 239773.416666667 1.01102871535267 0.997381341619588 35 235000 236547.026602457 239024.5 0.989635065034993 0.993459961747663 36 237384 236843.834938816 238306.208333333 0.993863469169582 1.00228068026902 37 238020 238946.507789878 237566.583333333 1.00580857979764 0.996122530525984 38 236412 236986.930894428 236843.791666667 1.00060436132505 0.997573997467883 39 232279 233059.849692799 236031.958333333 0.987408024483121 0.996649574374015 40 230408 230081.144711385 234814.208333333 0.979843367845825 1.00142060875534 41 230254 226148.373473478 233265.75 0.969488120195432 1.01815457022070 42 229217 224502.792477694 231530.541666667 0.969646556612428 1.02099843601177 43 239658 236435.61943304 229670.833333333 1.02945426722900 1.01362899792632 44 239906 235819.306287412 227726.916666667 1.03553549900555 1.01732976734147 45 236558 231791.037272209 225547 1.02768397394871 1.02056577676122 46 223566 225720.459563189 223258.208333333 1.01102871535267 0.990455187060323 47 216054 218503.628983589 220792.125 0.989635065034993 0.98878906956839 48 214685 216545.747198187 217882.791666667 0.993863469169582 0.991407140420617 49 216086 216177.935151617 214929.5 1.00580857979764 0.9995747246288 50 211692 212424.345183711 212296.041666667 1.00060436132505 0.996552442315037 51 204681 206854.781279035 209492.708333333 0.987408024483121 0.989491268871842 52 203075 202619.727869681 206787.875 0.979843367845825 1.00224692893977 53 198401 198300.150383571 204541.083333333 0.969488120195432 1.00050857054941 54 191246 196411.727713233 202560.125 0.969646556612428 0.97369949455984 55 206750 206688.723396830 200775.041666667 1.02945426722900 1.00029646805188 56 209611 206091.110034649 199018.875 1.03553549900555 1.01707929063393 57 199573 202794.591385921 197331.666666667 1.02768397394871 0.984114017223513 58 195635 197895.137890235 195736.416666667 1.01102871535267 0.988579113593541 59 190062 192068.208482814 194079.833333333 0.989635065034993 0.989554708201522 60 193134 191571.780300982 192754.625 0.993863469169582 1.00815474855724 61 194795 192947.947827374 191833.666666667 1.00580857979764 1.00957280029886 62 190835 190931.488577994 190816.166666667 1.00060436132505 0.999494642928136 63 185045 187447.194273818 189837.625 0.987408024483121 0.987184688023078 64 184425 185180.026513885 188989.416666667 0.979843367845825 0.995922743245595 65 177293 182625.022107529 188372.625 0.969488120195432 0.970803441686159 66 180549 182420.212724594 188130.625 0.969646556612428 0.989742295019582 67 195344 193743.507562136 188200.208333333 1.02945426722900 1.00826088294778 68 196597 NA NA 1.03553549900555 NA 69 189102 NA NA 1.02768397394871 NA 70 185749 NA NA 1.01102871535267 NA 71 185145 NA NA 0.989635065034993 NA 72 192243 NA NA 0.993863469169582 NA 73 197356 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/1v77p1244110161.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/1v77p1244110161.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/2svn41244110161.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/2svn41244110161.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/3zm4g1244110161.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/3zm4g1244110161.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/4ek511244110161.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/04/t1244110339ccw8mgdnkral3lf/4ek511244110161.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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