Klassieke Decompositie- Bruin brood - Nhu Truong

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 23 May 2008 06:33:46 -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/23/t12115461005nyis6sm1waqz1x.htm/, Retrieved Fri, 23 May 2008 14:35:05 +0200

User-defined keywords:

Dataseries X:

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1,44 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,48 1,57 1,58 1,58 1,58 1,58 1,59 1,6 1,6 1,61 1,61 1,61 1,62 1,63 1,63 1,64 1,64 1,64 1,64 1,64 1,65 1,65 1,65 1,65

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 5 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.44 NA NA 1.00102301380294 NA 2 1.48 NA NA 0.99975803105593 NA 3 1.48 NA NA 0.997108398665167 NA 4 1.48 NA NA 0.994349527044258 NA 5 1.48 NA NA 0.99162114019264 NA 6 1.48 NA NA 0.988922735614117 NA 7 1.48 1.45781575428464 1.47833333333333 0.986121141567964 1.0152174550523 8 1.48 1.49840428587298 1.48 1.01243532829255 0.987717409749494 9 1.48 1.49829496402544 1.48 1.01236146217935 0.98778947772988 10 1.48 1.49322171239263 1.48 1.00893358945448 0.991145512898118 11 1.48 1.48801711496336 1.48 1.00541696956984 0.994612215892722 12 1.48 1.48288402058992 1.48 1.00194866256075 0.998055127339785 13 1.48 1.48151406042836 1.48 1.00102301380294 0.998978031684749 14 1.48 1.47964188596278 1.48 0.99975803105593 1.00024202750721 15 1.48 1.47572043002445 1.48 0.997108398665167 1.00289998694094 16 1.48 1.4716373000255 1.48 0.994349527044258 1.00568258223297 17 1.48 1.46759928748511 1.48 0.99162114019264 1.00844965830976 18 1.48 1.46360564870889 1.48 0.988922735614117 1.01120134464196 19 1.48 1.45945928952059 1.48 0.986121141567964 1.01407419215247 20 1.48 1.49840428587298 1.48 1.01243532829255 0.987717409749494 21 1.48 1.49829496402544 1.48 1.01236146217935 0.98778947772988 22 1.48 1.49322171239263 1.48 1.00893358945448 0.991145512898118 23 1.48 1.48801711496336 1.48 1.00541696956984 0.994612215892722 24 1.48 1.48288402058992 1.48 1.00194866256075 0.998055127339785 25 1.48 1.48151406042836 1.48 1.00102301380294 0.998978031684749 26 1.48 1.48339097857924 1.48375 0.99975803105593 0.997714035862288 27 1.48 1.48735336134221 1.49166666666667 0.997108398665167 0.995056076428555 28 1.48 1.49152429056639 1.5 0.994349527044258 0.992273481136529 29 1.48 1.49569521979057 1.50833333333333 0.99162114019264 0.98950640505974 30 1.48 1.49986614901474 1.51666666666667 0.988922735614117 0.986754718727538 31 1.48 1.50424562470013 1.52541666666667 0.986121141567964 0.983881871217033 32 1.57 1.55408822892907 1.535 1.01243532829255 1.01023865362000 33 1.58 1.5640984590671 1.545 1.01236146217935 1.01016658563962 34 1.58 1.56931212059732 1.55541666666667 1.00893358945448 1.00681055047138 35 1.58 1.57473432858876 1.56625 1.00541696956984 1.00334384747678 36 1.58 1.58015653658019 1.57708333333333 1.00194866256075 0.999900936029713 37 1.59 1.58995822025701 1.58833333333333 1.00102301380294 1.00002627725839 38 1.6 1.59628032291930 1.59666666666667 0.99975803105593 1.00233021545608 39 1.6 1.59661982336260 1.60125 0.997108398665167 1.00211708296987 40 1.61 1.59675961551190 1.60583333333333 0.994349527044258 1.00829203366585 41 1.61 1.59733638666031 1.61083333333333 0.99162114019264 1.00792795646894 42 1.61 1.59793432029648 1.61583333333333 0.988922735614117 1.00755079827141 43 1.62 1.59792713314909 1.62041666666667 0.986121141567964 1.01381343766747 44 1.63 1.64436371236849 1.62416666666667 1.01243532829255 0.99126488120575 45 1.63 1.64804009697280 1.62791666666667 1.01236146217935 0.989053605548833 46 1.64 1.64624330679323 1.63166666666667 1.00893358945448 0.99620754309678 47 1.64 1.64385674524668 1.635 1.00541696956984 0.99765384346426 48 1.64 1.64152589216204 1.63833333333333 1.00194866256075 0.999070442830466 49 1.64 NA NA NA NA 50 1.64 NA NA NA NA 51 1.65 NA NA NA NA 52 1.65 NA NA NA NA 53 1.65 NA NA NA NA 54 1.65 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/150sr1211546020.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/150sr1211546020.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/2vt431211546020.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/2vt431211546020.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/3x3w71211546020.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/3x3w71211546020.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/4mbxl1211546020.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/23/t12115461005nyis6sm1waqz1x/4mbxl1211546020.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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