Opgave 9-classical decomposition eigen gegevens-Messelis Peter

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 09:00:53 -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/t1211727770alzvzu1n68ne26c.htm/, Retrieved Sun, 25 May 2008 17:02:50 +0200

User-defined keywords:

Dataseries X:

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0,76 0,77 0,76 0,77 0,78 0,79 0,78 0,76 0,78 0,76 0,74 0,73 0,72 0,71 0,73 0,75 0,75 0,72 0,72 0,72 0,74 0,78 0,74 0,74 0,75 0,78 0,81 0,75 0,7 0,71 0,71 0,73 0,74 0,74 0,75 0,74 0,74 0,73 0,76 0,8 0,83 0,81 0,83 0,88 0,89 0,93 0,91 0,9 0,86 0,88 0,93 0,98 0,97 1,03 1,06 1,06 1,08 1,09 1,04 1

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 0.76 NA NA -0.0114351851851852 NA 2 0.77 NA NA -0.0104629629629629 NA 3 0.76 NA NA 0.0130092592592593 NA 4 0.77 NA NA 0.00912037037037049 NA 5 0.78 NA NA -0.00226851851851855 NA 6 0.79 NA NA -0.0203240740740741 NA 7 0.78 0.74537037037037 0.763333333333333 -0.0179629629629630 0.0346296296296296 8 0.76 0.760231481481482 0.759166666666667 0.00106481481481486 -0.000231481481481666 9 0.78 0.764675925925926 0.755416666666667 0.00925925925925925 0.0153240740740742 10 0.76 0.783287037037037 0.753333333333333 0.0299537037037036 -0.0232870370370369 11 0.74 0.758287037037037 0.75125 0.0070370370370369 -0.0182870370370370 12 0.73 0.740092592592593 0.747083333333333 -0.00699074074074066 -0.0100925925925927 13 0.72 0.730231481481481 0.741666666666667 -0.0114351851851852 -0.0102314814814815 14 0.71 0.727037037037037 0.7375 -0.0104629629629629 -0.0170370370370371 15 0.73 0.747175925925926 0.734166666666667 0.0130092592592593 -0.017175925925926 16 0.75 0.742453703703704 0.733333333333333 0.00912037037037049 0.00754629629629633 17 0.75 0.731898148148148 0.734166666666667 -0.00226851851851855 0.0181018518518518 18 0.72 0.714259259259259 0.734583333333333 -0.0203240740740741 0.00574074074074082 19 0.72 0.718287037037037 0.73625 -0.0179629629629630 0.00171296296296297 20 0.72 0.741481481481481 0.740416666666667 0.00106481481481486 -0.0214814814814814 21 0.74 0.755925925925926 0.746666666666667 0.00925925925925925 -0.015925925925926 22 0.78 0.779953703703704 0.75 0.0299537037037036 4.62962962963775e-05 23 0.74 0.754953703703704 0.747916666666667 0.0070370370370369 -0.0149537037037037 24 0.74 0.738425925925926 0.745416666666667 -0.00699074074074066 0.00157407407407406 25 0.75 0.733148148148148 0.744583333333333 -0.0114351851851852 0.0168518518518518 26 0.78 0.73412037037037 0.744583333333333 -0.0104629629629629 0.0458796296296297 27 0.81 0.75800925925926 0.745 0.0130092592592593 0.0519907407407407 28 0.75 0.752453703703704 0.743333333333333 0.00912037037037049 -0.00245370370370368 29 0.7 0.739814814814815 0.742083333333333 -0.00226851851851855 -0.0398148148148147 30 0.71 0.722175925925926 0.7425 -0.0203240740740741 -0.0121759259259260 31 0.71 0.72412037037037 0.742083333333333 -0.0179629629629630 -0.0141203703703703 32 0.73 0.740648148148148 0.739583333333333 0.00106481481481486 -0.0106481481481482 33 0.74 0.744675925925926 0.735416666666667 0.00925925925925925 -0.00467592592592592 34 0.74 0.76537037037037 0.735416666666667 0.0299537037037036 -0.0253703703703703 35 0.75 0.749953703703704 0.742916666666667 0.0070370370370369 4.62962962963775e-05 36 0.74 0.745509259259259 0.7525 -0.00699074074074066 -0.00550925925925916 37 0.74 0.750231481481481 0.761666666666666 -0.0114351851851852 -0.0102314814814813 38 0.73 0.762453703703704 0.772916666666667 -0.0104629629629629 -0.0324537037037037 39 0.76 0.798425925925926 0.785416666666667 0.0130092592592593 -0.0384259259259259 40 0.8 0.808703703703704 0.799583333333333 0.00912037037037049 -0.00870370370370366 41 0.83 0.811898148148148 0.814166666666667 -0.00226851851851855 0.0181018518518519 42 0.81 0.807175925925926 0.8275 -0.0203240740740741 0.00282407407407415 43 0.83 0.821203703703704 0.839166666666667 -0.0179629629629630 0.0087962962962963 44 0.88 0.851481481481482 0.850416666666667 0.00106481481481486 0.0285185185185185 45 0.89 0.87300925925926 0.86375 0.00925925925925925 0.0169907407407408 46 0.93 0.908287037037037 0.878333333333334 0.0299537037037036 0.0217129629629629 47 0.91 0.898703703703704 0.891666666666667 0.0070370370370369 0.0112962962962962 48 0.9 0.899675925925926 0.906666666666667 -0.00699074074074066 0.000324074074074199 49 0.86 0.913981481481481 0.925416666666667 -0.0114351851851852 -0.0539814814814814 50 0.88 0.932037037037037 0.9425 -0.0104629629629629 -0.052037037037037 51 0.93 0.970925925925926 0.957916666666667 0.0130092592592593 -0.0409259259259259 52 0.98 0.98162037037037 0.9725 0.00912037037037049 -0.00162037037037033 53 0.97 0.982314814814815 0.984583333333333 -0.00226851851851855 -0.0123148148148149 54 1.03 0.973842592592593 0.994166666666667 -0.0203240740740741 0.0561574074074076 55 1.06 NA NA -0.0179629629629630 NA 56 1.06 NA NA 0.00106481481481486 NA 57 1.08 NA NA 0.00925925925925925 NA 58 1.09 NA NA 0.0299537037037036 NA 59 1.04 NA NA 0.0070370370370369 NA 60 1 NA NA -0.00699074074074066 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/1pd2x1211727638.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/1pd2x1211727638.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/2ghxs1211727638.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/2ghxs1211727638.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/3ogok1211727638.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/3ogok1211727638.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/4ghgj1211727638.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/25/t1211727770alzvzu1n68ne26c/4ghgj1211727638.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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