opgave 9, oef 2

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 09:26:20 -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/t12117292611srte2oyne8y6kt.htm/, Retrieved Sun, 25 May 2008 17:27:46 +0200

User-defined keywords:

Dataseries X:

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-22 -31 -22 -26 -19 -20 -24 -29 -28 -31 -30 -32 -38 -43 -51 -43 -43 -42 -47 -45 -38 -46 -38 -32 -27 -26 -21 -23 -24 -17 -23 -16 -22 -26 -25 -21 -21 -18 -12 -19 -31 -38 -38 -32 -43 -33 -28 -25 -19 -20 -21 -19 -17 -16 -10 -16 -10 -8 -7 -15 -7 -6 -6 2 -4 -4 -8 -10 -16 -14 -30 -33

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 6 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 -22 NA NA 0.878593528797878 NA 2 -31 NA NA 0.891862724105373 NA 3 -22 NA NA 0.86922906834002 NA 4 -26 NA NA 0.907834792939273 NA 5 -19 NA NA 1.02869071623239 NA 6 -20 NA NA 1.02067951940671 NA 7 -24 -27.8337680645636 -26.8333333333333 1.03728328190920 0.862261981357653 8 -29 -28.9410817048124 -28 1.03361006088616 1.0020358014185 9 -28 -31.9872962682127 -29.7083333333333 1.07671123483465 0.875347505622878 10 -31 -34.5283393728736 -31.625 1.09180519756122 0.897813232928151 11 -30 -33.339932427394 -33.3333333333333 1.00019797282182 0.899821859727295 12 -32 -41.0134420513267 -35.25 1.16350190216530 0.78023200198494 13 -38 -32.6177847566212 -37.125 0.878593528797878 1.16500860752925 14 -43 -34.5596805590832 -38.75 0.891862724105373 1.24422446343181 15 -51 -34.6242912222108 -39.8333333333333 0.86922906834002 1.47295433927278 16 -43 -37.1077471613928 -40.875 0.907834792939273 1.15878767344673 17 -43 -43.0335616290551 -41.8333333333333 1.02869071623239 0.999220105708554 18 -42 -43.0386530683164 -42.1666666666667 1.02067951940671 0.975866970867613 19 -47 -43.263356882963 -41.7083333333333 1.03728328190920 1.08636969912310 20 -45 -41.9042745517597 -40.5416666666667 1.03361006088616 1.07387612555890 21 -38 -41.5431084773702 -38.5833333333333 1.07671123483465 0.91471248524168 22 -46 -39.8508897109845 -36.5 1.09180519756122 1.15430296120391 23 -38 -34.8819043021609 -34.875 1.00019797282182 1.08939006514177 24 -32 -38.4440420173784 -33.0416666666667 1.16350190216530 0.83237865533324 25 -27 -27.2363993927342 -31 0.878593528797878 0.991320460927105 26 -26 -25.6782142648672 -28.7916666666667 0.891862724105373 1.01253146857541 27 -21 -23.3967490894855 -26.9166666666667 0.86922906834002 0.897560593554314 28 -23 -23.0741343205399 -25.4166666666667 0.907834792939273 0.996787124513102 29 -24 -24.7314393027538 -24.0416666666667 1.02869071623239 0.970424717550816 30 -17 -23.518157259663 -23.0416666666667 1.02067951940671 0.722845749022923 31 -23 -23.1659932959722 -22.3333333333333 1.03728328190920 0.992834613484884 32 -16 -22.4810188242740 -21.75 1.03361006088616 0.711711516504935 33 -22 -22.6557988996457 -21.0416666666667 1.07671123483465 0.971053817058025 34 -26 -22.382006550005 -20.5 1.09180519756122 1.16164741270680 35 -25 -20.62908318945 -20.625 1.00019797282182 1.21188129256201 36 -21 -25.3546456180188 -21.7916666666667 1.16350190216530 0.828250582413029 37 -21 -20.4639076082506 -23.2916666666667 0.878593528797878 1.02619697088220 38 -18 -21.9249586342571 -24.5833333333333 0.891862724105373 0.820982164676723 39 -12 -22.7086094103830 -26.125 0.86922906834002 0.528433942525483 40 -19 -24.776324557301 -27.2916666666667 0.907834792939273 0.766861120020368 41 -31 -28.5033052622726 -27.7083333333333 1.02869071623239 1.08759316559094 42 -38 -28.5790265433880 -28 1.02067951940671 1.32964640843555 43 -38 -29.1303721669501 -28.0833333333333 1.03728328190920 1.30448041591150 44 -32 -29.0272158765530 -28.0833333333333 1.03361006088616 1.10241368431922 45 -43 -30.7311331609056 -28.5416666666667 1.07671123483465 1.39923249087027 46 -33 -31.5713669628119 -28.9166666666667 1.09180519756122 1.04525090848524 47 -28 -28.3389425632849 -28.3333333333333 1.00019797282182 0.988039689112324 48 -25 -31.2206343747688 -26.8333333333333 1.16350190216530 0.800752467099257 49 -19 -21.7451898377475 -24.75 0.878593528797878 0.873756455646935 50 -20 -20.4385207607481 -22.9166666666667 0.891862724105373 0.97854439830155 51 -21 -18.1451568015979 -20.875 0.86922906834002 1.15733361963291 52 -19 -16.7571172196707 -18.4583333333333 0.907834792939273 1.13384657700529 53 -17 -17.0162589310108 -16.5416666666667 1.02869071623239 0.999044506135176 54 -16 -15.5653626709524 -15.25 1.02067951940671 1.02792336665941 55 -10 -14.8677270406986 -14.3333333333333 1.03728328190920 0.672597766465999 56 -16 -13.6953333067416 -13.25 1.03361006088616 1.16828116860244 57 -10 -12.9653977861339 -12.0416666666667 1.07671123483465 0.771283701815512 58 -8 -11.5094464576245 -10.5416666666667 1.09180519756122 0.695081212589537 59 -7 -9.1268065019991 -9.125 1.00019797282182 0.766971448169384 60 -15 -9.40497370916949 -8.08333333333333 1.16350190216530 1.59490079013996 61 -7 -6.58945146598409 -7.5 0.878593528797878 1.06230390133917 62 -6 -6.3916828560885 -7.16666666666667 0.891862724105373 0.938719916975323 63 -6 -6.22947498977015 -7.16666666666667 0.86922906834002 0.9631630289636 64 2 -6.96006674586776 -7.66666666666667 0.907834792939273 -0.287353566140355 65 -4 -9.12963010656249 -8.875 1.02869071623239 0.43813385135119 66 -4 -10.8021915803877 -10.5833333333333 1.02067951940671 0.370295228540691 67 -8 NA NA 1.03728328190920 NA 68 -10 NA NA 1.03361006088616 NA 69 -16 NA NA 1.07671123483465 NA 70 -14 NA NA 1.09180519756122 NA 71 -30 NA NA 1.00019797282182 NA 72 -33 NA NA 1.16350190216530 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/14fwg1211729173.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/14fwg1211729173.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/25ad81211729173.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/25ad81211729173.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/3697b1211729173.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/3697b1211729173.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/4b3u41211729173.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t12117292611srte2oyne8y6kt/4b3u41211729173.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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