Opgave 9 Oefening 2

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 12 Jan 2010 11:59:49 -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/12/t1263322849q9zcxpwj8ob0vcg.htm/, Retrieved Tue, 12 Jan 2010 20:00:55 +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/12/t1263322849q9zcxpwj8ob0vcg.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 «

10,1200 10,1200 10,0500 10,1400 10,1700 10,2000 10,2000 10,3500 10,4300 10,5200 10,5700 10,5700 10,5700 10,6500 10,5700 10,6100 10,6300 10,7100 10,7200 10,7700 10,7900 10,8200 10,9000 10,8300 10,9200 10,9100 10,8800 10,8700 11,0000 10,9900 11,0300 11,0400 10,9900 10,9000 11,0000 10,9900 10,9200 10,9800 11,1500 11,1900 11,3300 11,3800 11,4000 11,4500 11,5600 11,6100 11,8200 11,7700 11,8500 11,8200 11,9200 11,8600 11,8700 11,9400 11,8600 11,9200 11,8300 11,9100 11,9300 11,9900 11,9600 12,1200 11,8500 12,0100 12,1000 12,2100 12,3100 12,3100 12,3900 12,3500 12,4100 12,5100

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 10.12 NA NA -0.00968750000000013 NA 2 10.12 NA NA 0.00839583333333345 NA 3 10.05 NA NA -0.0462708333333329 NA 4 10.14 NA NA -0.043854166666667 NA 5 10.17 NA NA 0.00356249999999919 NA 6 10.2 NA NA 0.032062500000001 NA 7 10.2 10.2868125 10.3054166666667 -0.0186041666666669 -0.0868125000000024 8 10.35 10.3596458333333 10.34625 0.0133958333333328 -0.00964583333333202 9 10.43 10.3857291666667 10.39 -0.00427083333333306 0.0442708333333321 10 10.52 10.4283958333333 10.43125 -0.00285416666666626 0.0916041666666665 11 10.57 10.5274791666667 10.47 0.0574791666666666 0.0425208333333327 12 10.57 10.5210625 10.5104166666667 0.0106458333333332 0.0489374999999992 13 10.57 10.5436458333333 10.5533333333333 -0.00968750000000013 0.0263541666666658 14 10.65 10.6008958333333 10.5925 0.00839583333333345 0.0491041666666678 15 10.57 10.5787291666667 10.625 -0.0462708333333329 -0.0087291666666669 16 10.61 10.6086458333333 10.6525 -0.043854166666667 0.00135416666666721 17 10.63 10.6823125 10.67875 0.00356249999999919 -0.0523124999999993 18 10.71 10.7353958333333 10.7033333333333 0.032062500000001 -0.0253958333333326 19 10.72 10.7101458333333 10.72875 -0.0186041666666669 0.00985416666666872 20 10.77 10.7675625 10.7541666666667 0.0133958333333328 0.00243749999999920 21 10.79 10.7736458333333 10.7779166666667 -0.00427083333333306 0.016354166666666 22 10.82 10.7988125 10.8016666666667 -0.00285416666666626 0.0211874999999999 23 10.9 10.8853958333333 10.8279166666667 0.0574791666666666 0.0146041666666683 24 10.83 10.8656458333333 10.855 0.0106458333333332 -0.0356458333333336 25 10.92 10.8698958333333 10.8795833333333 -0.00968750000000013 0.0501041666666655 26 10.91 10.9121458333333 10.90375 0.00839583333333345 -0.00214583333333351 27 10.88 10.8770625 10.9233333333333 -0.0462708333333329 0.00293749999999982 28 10.87 10.8911458333333 10.935 -0.043854166666667 -0.0211458333333319 29 11 10.9460625 10.9425 0.00356249999999919 0.0539375 30 10.99 10.9853958333333 10.9533333333333 0.032062500000001 0.00460416666666852 31 11.03 10.9413958333333 10.96 -0.0186041666666669 0.0886041666666664 32 11.04 10.9763125 10.9629166666667 0.0133958333333328 0.0636875000000003 33 10.99 10.9728125 10.9770833333333 -0.00427083333333306 0.0171875000000004 34 10.9 10.9988125 11.0016666666667 -0.00285416666666626 -0.098812500000001 35 11 11.0862291666667 11.02875 0.0574791666666666 -0.0862291666666675 36 10.99 11.0693958333333 11.05875 0.0106458333333332 -0.0793958333333329 37 10.92 11.0807291666667 11.0904166666667 -0.00968750000000013 -0.160729166666666 38 10.98 11.1313125 11.1229166666667 0.00839583333333345 -0.151312500000001 39 11.15 11.1174791666667 11.16375 -0.0462708333333329 0.0325208333333347 40 11.19 11.1732291666667 11.2170833333333 -0.043854166666667 0.0167708333333341 41 11.33 11.2843958333333 11.2808333333333 0.00356249999999919 0.0456041666666671 42 11.38 11.3795625 11.3475 0.032062500000001 0.000437500000000313 43 11.4 11.4001458333333 11.41875 -0.0186041666666669 -0.000145833333334622 44 11.45 11.5058958333333 11.4925 0.0133958333333328 -0.0558958333333326 45 11.56 11.5553125 11.5595833333333 -0.00427083333333306 0.00468749999999929 46 11.61 11.6167291666667 11.6195833333333 -0.00285416666666626 -0.00672916666666978 47 11.82 11.7274791666667 11.67 0.0574791666666666 0.0925208333333316 48 11.77 11.7264791666667 11.7158333333333 0.0106458333333332 0.0435208333333357 49 11.85 11.7486458333333 11.7583333333333 -0.00968750000000013 0.101354166666669 50 11.82 11.8054791666667 11.7970833333333 0.00839583333333345 0.0145208333333358 51 11.92 11.7816458333333 11.8279166666667 -0.0462708333333329 0.138354166666666 52 11.86 11.8078125 11.8516666666667 -0.043854166666667 0.0521875000000005 53 11.87 11.8723125 11.86875 0.00356249999999919 -0.00231250000000038 54 11.94 11.9145625 11.8825 0.032062500000001 0.0254374999999989 55 11.86 11.8776458333333 11.89625 -0.0186041666666669 -0.0176458333333347 56 11.92 11.9267291666667 11.9133333333333 0.0133958333333328 -0.00672916666666445 57 11.83 11.9186458333333 11.9229166666667 -0.00427083333333306 -0.0886458333333309 58 11.91 11.9233958333333 11.92625 -0.00285416666666626 -0.0133958333333322 59 11.93 11.9995625 11.9420833333333 0.0574791666666666 -0.0695625 60 11.99 11.9735625 11.9629166666667 0.0106458333333332 0.0164374999999986 61 11.96 11.9832291666667 11.9929166666667 -0.00968750000000013 -0.0232291666666669 62 12.12 12.0363125 12.0279166666667 0.00839583333333345 0.0836874999999999 63 11.85 12.0212291666667 12.0675 -0.0462708333333329 -0.171229166666667 64 12.01 12.0653125 12.1091666666667 -0.043854166666667 -0.0553124999999994 65 12.1 12.1510625 12.1475 0.00356249999999919 -0.0510625000000005 66 12.21 12.2212291666667 12.1891666666667 0.032062500000001 -0.0112291666666646 67 12.31 NA NA -0.0186041666666669 NA 68 12.31 NA NA 0.0133958333333328 NA 69 12.39 NA NA -0.00427083333333306 NA 70 12.35 NA NA -0.00285416666666626 NA 71 12.41 NA NA 0.0574791666666666 NA 72 12.51 NA NA 0.0106458333333332 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/166xs1263322786.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/166xs1263322786.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/2iwr21263322786.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/2iwr21263322786.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/3bmmp1263322786.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/3bmmp1263322786.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/4m8m31263322786.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/12/t1263322849q9zcxpwj8ob0vcg/4m8m31263322786.ps (open in new window)

Parameters (Session):

par1 = additive ; par2 = 12 ;

Parameters (R input):

par1 = additive ; 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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