Classical Decomposition - Niels Braspennincx - Gem p badpak

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

Title produced by software: Classical Decomposition

Date of computation: Sat, 31 May 2008 14:27:03 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34.htm/, Retrieved Sat, 31 May 2008 20:32:05 +0000

User-defined keywords:

Dataseries X:

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38 38 37.93 38 38.02 38.02 38.02 37.96 37.96 37.99 38 38 38 38.01 38.06 38.02 38.05 38.05 38.05 38.05 38.03 37.98 38.03 38.04 38.04 38.08 38.14 38.37 38.49 38.55 38.55 38.55 38.48 38.51 38.48 38.48 38.48 38.43 38.43 38.45 38.48 38.47 38.47 38.42 38.55 38.56 38.57 38.57 38.57 38.57 38.62 38.73 38.74 38.68 38.69 38.69 38.61 38.77 38.78 38.81 38.81 38.81 38.76 38.93 38.95 38.97 38.97 38.96 38.92 38.95 38.95 38.97 38.97 39.05 39.08 38.83 38.86 38.87 38.87 38.75 38.86 38.93 38.96 38.95

Text written by user:

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 38 NA NA -0.0345694444444452 NA 2 38 NA NA -0.0508194444444446 NA 3 37.93 NA NA -0.0451527777777789 NA 4 38 NA NA 0.0368472222222219 NA 5 38.02 NA NA 0.062930555555557 NA 6 38.02 NA NA 0.0489305555555598 NA 7 38.02 38.0264305555556 37.9916666666667 0.034763888888889 -0.0064305555555535 8 37.96 37.9980972222222 37.9920833333333 0.00601388888888816 -0.0380972222222198 9 37.96 37.9707638888889 37.9979166666667 -0.0271527777777768 -0.0107638888888815 10 37.99 37.9977638888889 38.0041666666667 -0.00640277777777859 -0.00776388888888846 11 38 37.9943472222222 38.00625 -0.0119027777777778 0.00565277777776885 12 38 37.9952638888889 38.00875 -0.013486111111114 0.00473611111110728 13 38 37.9766805555556 38.01125 -0.0345694444444452 0.0233194444444393 14 38.01 37.9654305555556 38.01625 -0.0508194444444446 0.0445694444444413 15 38.06 37.9777638888889 38.0229166666667 -0.0451527777777789 0.082236111111122 16 38.02 38.0622638888889 38.0254166666667 0.0368472222222219 -0.0422638888888827 17 38.05 38.0891805555556 38.02625 0.062930555555557 -0.0391805555555607 18 38.05 38.0780972222222 38.0291666666667 0.0489305555555598 -0.0280972222222218 19 38.05 38.0672638888889 38.0325 0.034763888888889 -0.0172638888888912 20 38.05 38.0430972222222 38.0370833333333 0.00601388888888816 0.00690277777777482 21 38.03 38.0161805555556 38.0433333333333 -0.0271527777777768 0.0138194444444437 22 37.98 38.0548472222222 38.06125 -0.00640277777777859 -0.0748472222222247 23 38.03 38.0822638888889 38.0941666666667 -0.0119027777777778 -0.0522638888888878 24 38.04 38.1198472222222 38.1333333333333 -0.013486111111114 -0.0798472222222202 25 38.04 38.1404305555556 38.175 -0.0345694444444452 -0.100430555555555 26 38.08 38.1658472222222 38.2166666666667 -0.0508194444444446 -0.0858472222222275 27 38.14 38.2110972222222 38.25625 -0.0451527777777789 -0.071097222222221 28 38.37 38.3339305555556 38.2970833333333 0.0368472222222219 0.0360694444444363 29 38.49 38.4008472222222 38.3379166666667 0.062930555555557 0.0891527777777767 30 38.55 38.4239305555556 38.375 0.0489305555555598 0.126069444444447 31 38.55 38.4464305555556 38.4116666666667 0.034763888888889 0.103569444444446 32 38.55 38.4505972222222 38.4445833333333 0.00601388888888816 0.099402777777783 33 38.48 38.4440972222222 38.47125 -0.0271527777777768 0.0359027777777854 34 38.51 38.4802638888889 38.4866666666667 -0.00640277777777859 0.0297361111111059 35 38.48 38.4776805555556 38.4895833333333 -0.0119027777777778 0.00231944444444565 36 38.48 38.4723472222222 38.4858333333333 -0.013486111111114 0.00765277777777129 37 38.48 38.4445972222222 38.4791666666667 -0.0345694444444452 0.0354027777777759 38 38.43 38.4195972222222 38.4704166666667 -0.0508194444444446 0.0104027777777773 39 38.43 38.4227638888889 38.4679166666667 -0.0451527777777789 0.00723611111111211 40 38.45 38.5097638888889 38.4729166666667 0.0368472222222219 -0.0597638888888739 41 38.48 38.5416805555556 38.47875 0.062930555555557 -0.0616805555555544 42 38.47 38.5351805555555 38.48625 0.0489305555555598 -0.0651805555555498 43 38.47 38.5285138888889 38.49375 0.034763888888889 -0.0585138888888892 44 38.42 38.5093472222222 38.5033333333333 0.00601388888888816 -0.0893472222222229 45 38.55 38.4899305555556 38.5170833333333 -0.0271527777777768 0.0600694444444443 46 38.56 38.5302638888889 38.5366666666667 -0.00640277777777859 0.0297361111111201 47 38.57 38.5472638888889 38.5591666666667 -0.0119027777777778 0.0227361111111151 48 38.57 38.5652638888889 38.57875 -0.013486111111114 0.00473611111111438 49 38.57 38.5620972222222 38.5966666666667 -0.0345694444444452 0.00790277777777249 50 38.57 38.5662638888889 38.6170833333333 -0.0508194444444446 0.00373611111110961 51 38.62 38.5856805555556 38.6308333333333 -0.0451527777777789 0.0343194444444421 52 38.73 38.6789305555556 38.6420833333333 0.0368472222222219 0.0510694444444439 53 38.74 38.7225138888889 38.6595833333333 0.062930555555557 0.0174861111111113 54 38.68 38.7272638888889 38.6783333333333 0.0489305555555598 -0.0472638888888852 55 38.69 38.7330972222222 38.6983333333333 0.034763888888889 -0.0430972222222223 56 38.69 38.7243472222222 38.7183333333333 0.00601388888888816 -0.0343472222222232 57 38.61 38.7070138888889 38.7341666666667 -0.0271527777777768 -0.0970138888888883 58 38.77 38.7419305555556 38.7483333333333 -0.00640277777777859 0.0280694444444478 59 38.78 38.7535138888889 38.7654166666667 -0.0119027777777778 0.0264861111111045 60 38.81 38.7727638888889 38.78625 -0.013486111111114 0.0372361111111132 61 38.81 38.7754305555556 38.81 -0.0345694444444452 0.0345694444444504 62 38.81 38.7820972222222 38.8329166666667 -0.0508194444444446 0.0279027777777827 63 38.76 38.8119305555556 38.8570833333333 -0.0451527777777789 -0.0519305555555576 64 38.93 38.9143472222222 38.8775 0.0368472222222219 0.0156527777777740 65 38.95 38.9550138888889 38.8920833333333 0.062930555555557 -0.00501388888889664 66 38.97 38.9547638888889 38.9058333333333 0.0489305555555598 0.0152361111111148 67 38.97 38.9539305555556 38.9191666666667 0.034763888888889 0.0160694444444474 68 38.96 38.9418472222222 38.9358333333333 0.00601388888888816 0.0181527777777859 69 38.92 38.9320138888889 38.9591666666667 -0.0271527777777768 -0.0120138888888803 70 38.95 38.9619305555556 38.9683333333333 -0.00640277777777859 -0.0119305555555513 71 38.95 38.9485138888889 38.9604166666667 -0.0119027777777778 0.00148611111111308 72 38.97 38.9390138888889 38.9525 -0.013486111111114 0.0309861111111118 73 38.97 38.9095972222222 38.9441666666667 -0.0345694444444452 0.0604027777777745 74 39.05 38.8804305555556 38.93125 -0.0508194444444446 0.169569444444441 75 39.08 38.8748472222222 38.92 -0.0451527777777789 0.205152777777776 76 38.83 38.9535138888889 38.9166666666667 0.0368472222222219 -0.123513888888894 77 38.86 38.9791805555556 38.91625 0.062930555555557 -0.119180555555566 78 38.87 38.9647638888889 38.9158333333333 0.0489305555555598 -0.0947638888888989 79 38.87 NA NA 0.034763888888889 NA 80 38.75 NA NA 0.00601388888888816 NA 81 38.86 NA NA -0.0271527777777768 NA 82 38.93 NA NA -0.00640277777777859 NA 83 38.96 NA NA -0.0119027777777778 NA 84 38.95 NA NA -0.013486111111114 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/1xxuz1212265618.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/1xxuz1212265618.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/2qmu21212265618.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/2qmu21212265618.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/3h1eo1212265618.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/3h1eo1212265618.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/4wc9w1212265618.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/31/t1212265925q8xfscpaf0ruy34/4wc9w1212265618.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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