*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 04 Dec 2009 09:38:19 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw.htm/, Retrieved Fri, 04 Dec 2009 17:39:34 +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/2009/Dec/04/t12599447674elo3tlvy1cuwbw.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 «

12008 9169 8788 8417 8247 8197 8236 8253 7733 8366 8626 8863 10102 8463 9114 8563 8872 8301 8301 8278 7736 7973 8268 9476 11100 8962 9173 8738 8459 8078 8411 8291 7810 8616 8312 9692 9911 8915 9452 9112 8472 8230 8384 8625 8221 8649 8625 10443 10357 8586 8892 8329 8101 7922 8120 7838 7735 8406 8209 9451 10041 9411 10405 8467 8464 8102 7627 7513 7510 8291 8064 9383

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 12008 NA NA 1572.86736111111 NA 2 9169 NA NA 149.309027777778 NA 3 8788 NA NA 697.134027777779 NA 4 8417 NA NA -65.7826388888885 NA 5 8247 NA NA -228.674305555556 NA 6 8197 NA NA -575.324305555555 NA 7 8236 8235.95069444444 8662.5 -426.549305555556 0.0493055555562023 8 8253 8108.09236111111 8553.66666666667 -445.574305555556 144.907638888890 9 7733 7666.76736111111 8537.83333333333 -871.065972222223 66.2326388888905 10 8366 8227.54236111111 8557.5 -329.957638888889 138.457638888889 11 8626 8263.44236111111 8589.625 -326.182638888889 362.557638888889 12 8863 9469.80069444444 8620 849.800694444444 -606.800694444444 13 10102 10199.9090277778 8627.04166666667 1572.86736111111 -97.9090277777777 14 8463 8780.10069444444 8630.79166666667 149.309027777778 -317.100694444443 15 9114 9329.09236111111 8631.95833333333 697.134027777779 -215.092361111110 16 8563 8549.92569444444 8615.70833333333 -65.7826388888885 13.0743055555558 17 8872 8355.74236111111 8584.41666666667 -228.674305555556 516.25763888889 18 8301 8019.71736111111 8595.04166666667 -575.324305555555 281.28263888889 19 8301 8235.61736111111 8662.16666666667 -426.549305555556 65.3826388888901 20 8278 8278.9673611111 8724.54166666666 -445.574305555556 -0.967361111108403 21 7736 7876.72569444444 8747.79166666667 -871.065972222223 -140.725694444443 22 7973 8427.58402777778 8757.54166666667 -329.957638888889 -454.584027777777 23 8268 8421.44236111111 8747.625 -326.182638888889 -153.442361111111 24 9476 9570.92569444444 8721.125 849.800694444444 -94.9256944444442 25 11100 10289.2840277778 8716.41666666667 1572.86736111111 810.71597222222 26 8962 8870.85069444444 8721.54166666667 149.309027777778 91.1493055555566 27 9173 9422.30069444444 8725.16666666667 697.134027777779 -249.300694444444 28 8738 8689.25902777778 8755.04166666667 -65.7826388888885 48.7409722222219 29 8459 8554.99236111111 8783.66666666667 -228.674305555556 -95.9923611111099 30 8078 8219.17569444445 8794.5 -575.324305555555 -141.175694444446 31 8411 8327.40902777778 8753.95833333333 -426.549305555556 83.5909722222223 32 8291 8256.88402777778 8702.45833333333 -445.574305555556 34.1159722222219 33 7810 7841.05902777778 8712.125 -871.065972222223 -31.0590277777792 34 8616 8409.37569444444 8739.33333333333 -329.957638888889 206.624305555555 35 8312 8429.27569444444 8755.45833333333 -326.182638888889 -117.275694444445 36 9692 9612.13402777778 8762.33333333333 849.800694444444 79.8659722222219 37 9911 10340.4090277778 8767.54166666667 1572.86736111111 -429.409027777780 38 8915 8929.64236111111 8780.33333333333 149.309027777778 -14.6423611111113 39 9452 9508.50902777778 8811.375 697.134027777779 -56.5090277777781 40 9112 8764.09236111111 8829.875 -65.7826388888885 347.907638888888 41 8472 8615.61736111111 8844.29166666667 -228.674305555556 -143.617361111112 42 8230 8313.30069444444 8888.625 -575.324305555555 -83.3006944444442 43 8384 8511.95069444444 8938.5 -426.549305555556 -127.950694444444 44 8625 8497.80069444444 8943.375 -445.574305555556 127.199305555556 45 8221 8035.26736111111 8906.33333333333 -871.065972222223 185.732638888889 46 8649 8520.4173611111 8850.375 -329.957638888889 128.582638888891 47 8625 8476.10902777778 8802.29166666667 -326.182638888889 148.890972222223 48 10443 9623.80069444444 8774 849.800694444444 819.199305555558 49 10357 10323.0340277778 8750.16666666667 1572.86736111111 33.9659722222223 50 8586 8855.68402777778 8706.375 149.309027777778 -269.684027777777 51 8892 9350.46736111111 8653.33333333333 697.134027777779 -458.46736111111 52 8329 8557.17569444444 8622.95833333333 -65.7826388888885 -228.175694444444 53 8101 8366.82569444444 8595.5 -228.674305555556 -265.825694444444 54 7922 7961.50902777778 8536.83333333333 -575.324305555555 -39.5090277777763 55 8120 8055.78402777778 8482.33333333333 -426.549305555556 64.2159722222241 56 7838 8057.96736111111 8503.54166666667 -445.574305555556 -219.967361111112 57 7735 7729.89236111111 8600.95833333333 -871.065972222223 5.10763888888869 58 8406 8339.79236111111 8669.75 -329.957638888889 66.207638888889 59 8209 8364.44236111111 8690.625 -326.182638888889 -155.442361111109 60 9451 9563.05069444444 8713.25 849.800694444444 -112.050694444444 61 10041 10273.0756944444 8700.20833333333 1572.86736111111 -232.075694444444 62 9411 8815.43402777778 8666.125 149.309027777778 595.565972222223 63 10405 9340.3423611111 8643.20833333333 697.134027777779 1064.65763888889 64 8467 8563.25902777778 8629.04166666667 -65.7826388888885 -96.259027777778 65 8464 8389.53402777778 8618.20833333333 -228.674305555556 74.4659722222241 66 8102 8034.00902777778 8609.33333333333 -575.324305555555 67.9909722222255 67 7627 NA NA -426.549305555556 NA 68 7513 NA NA -445.574305555556 NA 69 7510 NA NA -871.065972222223 NA 70 8291 NA NA -329.957638888889 NA 71 8064 NA NA -326.182638888889 NA 72 9383 NA NA 849.800694444444 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/1tp3k1259944697.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/1tp3k1259944697.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/20qcf1259944697.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/20qcf1259944697.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/34l4c1259944697.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/34l4c1259944697.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/4e7dv1259944697.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t12599447674elo3tlvy1cuwbw/4e7dv1259944697.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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