decomposition champagne Katrien Broux

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 25 May 2008 06:26:13 -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/25/t1211718419hq9llce776tdpu6.htm/, Retrieved Sun, 25 May 2008 14:26:59 +0200

User-defined keywords:

Dataseries X:

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2815 2672 2755 2721 2946 3036 2282 2212 2922 4301 5764 7312 2541 2475 3031 3266 3776 3230 3028 1759 3595 4474 6838 8357 3113 3006 4047 3523 3937 3986 3260 1573 3528 5211 7614 9254 5375 3088 3718 4514 4520 4539 3663 1643 4739 5428 8314 10651 3633 4292 4154 4121 4647 4753 3965 1723 5048 6922 9858 11331 4016 4276 4968 4677 3523 1821 5222 6872 10803 13916 2639 2899 3370 3740 2927 3986 4217 1738 5221 6424 9842 13076

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 13 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 2815 NA NA 0.827542628685895 NA 2 2672 NA NA 0.726000462117258 NA 3 2755 NA NA 0.850329372490055 NA 4 2721 NA NA 0.865344404325017 NA 5 2946 NA NA 0.936205334788187 NA 6 3036 NA NA 0.89182887170247 NA 7 2282 2585.24056050299 3466.75 0.74572454330511 0.882703155313333 8 2212 1243.64006556469 3447.125 0.36077602801311 1.77864967625951 9 2922 3060.67709407547 3450.41666666667 0.887045649774318 0.954690713912975 10 4301 3994.30976761687 3484.625 1.14626674824891 1.07678178464514 11 5764 6007.08270345892 3541.91666666667 1.69599775172357 0.959533984221833 12 7312 7409.11224004953 3584.58333333333 2.06693820482609 0.986892864232155 13 2541 2998.80760070051 3623.75 0.827542628685895 0.847336787930786 14 2475 2639.70743023910 3635.95833333333 0.726000462117258 0.937603907026857 15 3031 3099.55685389781 3645.125 0.850329372490055 0.977881724024001 16 3266 3184.79191206768 3680.375 0.865344404325017 1.02549871080261 17 3776 3494.23037787444 3732.33333333333 0.936205334788187 1.08063853600201 18 3230 3407.34368294825 3820.625 0.89182887170247 0.947952510973357 19 3028 2899.37702437027 3888 0.74572454330511 1.04436228008590 20 1759 1419.27786186907 3933.95833333333 0.36077602801311 1.23936266974780 21 3595 3546.77811015180 3998.41666666667 0.887045649774318 1.01359597030053 22 4474 4644.05196941596 4051.45833333333 1.14626674824891 0.963382845296336 23 6838 6900.80285204426 4068.875 1.69599775172357 0.990899196312259 24 8357 8489.08745207116 4107.08333333333 2.06693820482609 0.98444032379017 25 3113 3432.85370944626 4148.25 0.827542628685895 0.906825709302405 26 3006 3013.02291786364 4150.16666666667 0.726000462117258 0.99766914555412 27 4047 3520.04472859414 4139.625 0.850329372490055 1.14970129985147 28 3523 3606.35886104135 4167.54166666667 0.865344404325017 0.976885588968458 29 3937 3960.69468593266 4230.58333333333 0.936205334788187 0.994017542928312 30 3986 3835.12426507487 4300.29166666667 0.89182887170247 1.03934050750300 31 3260 3304.98903221631 4431.91666666667 0.74572454330511 0.986387539632427 32 1573 1634.16508355438 4529.58333333333 0.36077602801311 0.962571049785652 33 3528 4008.81801297799 4519.29166666667 0.887045649774318 0.88005990508389 34 5211 5211.93162094428 4546.875 1.14626674824891 0.999821252270361 35 7614 7822.718963252 4612.45833333333 1.69599775172357 0.973318872347009 36 9254 9631.50142236358 4659.79166666667 2.06693820482609 0.96080554777399 37 5375 3889.14002633795 4699.625 0.827542628685895 1.382053606607 38 3088 3426.23818088538 4719.33333333333 0.726000462117258 0.901280015273785 39 3718 4058.37408216139 4772.70833333333 0.850329372490055 0.916130431726956 40 4514 4181.52444178271 4832.20833333333 0.865344404325017 1.07951060978985 41 4520 4559.71006597463 4870.41666666667 0.936205334788187 0.991291098468967 42 4539 4421.50174821924 4957.79166666667 0.89182887170247 1.02657428594890 43 3663 3686.42713611687 4943.41666666667 0.74572454330511 0.993645029387032 44 1643 1775.37883385251 4921 0.36077602801311 0.925436289242417 45 4739 4425.76642860733 4989.33333333333 0.887045649774318 1.07077498924661 46 5428 5721.16062385386 4991.125 1.14626674824891 0.948758539896337 47 8314 8446.13947015639 4980.04166666667 1.69599775172357 0.984355045210502 48 10651 10322.8061294527 4994.25 2.06693820482609 1.03179308672774 49 3633 4150.74693983128 5015.75 0.827542628685895 0.875264151889654 50 4292 3652.99232522000 5031.66666666667 0.726000462117258 1.17492718787508 51 4154 4292.35638115823 5047.875 0.850329372490055 0.967766800127416 52 4121 4433.15938335706 5123 0.865344404325017 0.929585346168927 53 4647 4914.68792208182 5249.58333333333 0.936205334788187 0.945533078330551 54 4753 4764.37278985252 5342.25 0.89182887170247 0.997612951304578 55 3965 4016.87632436895 5386.54166666667 0.74572454330511 0.987085406624487 56 1723 1948.85197398882 5401.83333333333 0.36077602801311 0.884110246953978 57 5048 4821.16702699423 5435.08333333333 0.887045649774318 1.04704939109882 58 6922 6295.48802584107 5492.16666666667 1.14626674824891 1.09951761826681 59 9858 9274.56370530037 5468.5 1.69599775172357 1.06290714186007 60 11331 10953.7390164759 5299.5 2.06693820482609 1.03444129743795 61 4016 4327.8065814272 5229.70833333333 0.827542628685895 0.927952745678304 62 4276 3990.55229008528 5496.625 0.726000462117258 1.07153087822554 63 4968 5060.27466529779 5950.95833333333 0.850329372490055 0.981764889971173 64 4677 5609.30665290215 6482.16666666667 0.865344404325017 0.833792889105147 65 3523 6059.86208930585 6472.79166666667 0.936205334788187 0.581366365782023 66 1821 5191.03858588951 5820.66666666667 0.89182887170247 0.350796853051702 67 5222 4058.54368322612 5442.41666666667 0.74572454330511 1.28666842285878 68 6872 1945.72524841270 5393.16666666667 0.36077602801311 3.53184500514967 69 10803 4688.73850353001 5285.79166666667 0.887045649774318 2.30403124249022 70 13916 5928.44386082887 5171.95833333333 1.14626674824891 2.34732761693966 71 2639 8771.8417050603 5172.08333333333 1.69599775172357 0.300849022215895 72 2899 10742.9974420088 5197.54166666667 2.06693820482609 0.269850199225024 73 3370 NA 5194.04166666667 NA NA 74 3740 NA 5175.33333333333 NA NA 75 2927 NA 5116.625 NA NA 76 3986 NA 5041.58333333333 NA NA 77 4217 NA NA NA NA 78 1738 NA NA NA NA 79 5221 NA NA NA NA 80 6424 NA NA NA NA 81 9842 NA NA NA NA 82 13076 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/10jgp1211718358.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/10jgp1211718358.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/2i8as1211718358.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/2i8as1211718358.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/3wd371211718358.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/3wd371211718358.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/4ub2n1211718358.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211718419hq9llce776tdpu6/4ub2n1211718358.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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