*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 20 Jan 2010 09:02:54 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q.htm/, Retrieved Wed, 20 Jan 2010 17:27:11 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W52

Dataseries X:

» Textbox « » Textfile « » CSV «

4,26 4,26 4,07 4,26 4,4 4,46 4,34 4,18 4,11 3,98 3,85 3,66 3,59 3,57 3,76 3,6 3,43 3,26 3,3 3,31 3,14 3,3 3,49 3,39 3,37 3,54 3,7 3,96 4,03 4,02 4,04 3,92 3,79 3,83 3,76 3,82 4,06 4,11 4,01 4,22 4,34 4,64 4,62 4,44 4,39 4,42 4,28 4,41 4,25 4,23 4,23 4,37 4,51 4,84 4,85 4,58 4,56 4,46 4,26 3,87 4,13 4,24 4,03 3,93 4,03 4,12 3,92 3,77

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 7 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 4.26 NA NA -0.129644097222222 NA 2 4.26 NA NA -0.094123263888889 NA 3 4.07 NA NA -0.0404774305555556 NA 4 4.26 NA NA 0.0623350694444442 NA 5 4.4 NA NA 0.0930642361111113 NA 6 4.46 NA NA 0.199105902777778 NA 7 4.34 4.32837673611111 4.12458333333333 0.203793402777778 0.0116232638888887 8 4.18 4.11910590277778 4.06791666666667 0.0511892361111109 0.0608940972222216 9 4.11 3.97514756944444 4.02625 -0.0511024305555559 0.134852430555557 10 3.98 3.96098090277778 3.98583333333333 -0.0248524305555553 0.0190190972222224 11 3.85 3.82837673611111 3.91791666666667 -0.0895399305555552 0.0216232638888894 12 3.66 3.64775173611111 3.8275 -0.179748263888889 0.012248263888889 13 3.59 3.60452256944444 3.73416666666667 -0.129644097222222 -0.0145225694444435 14 3.57 3.56046006944444 3.65458333333333 -0.094123263888889 0.00953993055555546 15 3.76 3.53743923611111 3.57791666666667 -0.0404774305555556 0.222560763888889 16 3.6 3.57150173611111 3.50916666666667 0.0623350694444442 0.0284982638888889 17 3.43 3.55889756944444 3.46583333333333 0.0930642361111113 -0.128897569444444 18 3.26 3.63868923611111 3.43958333333333 0.199105902777778 -0.378689236111111 19 3.3 3.62296006944444 3.41916666666667 0.203793402777778 -0.322960069444444 20 3.31 3.45993923611111 3.40875 0.0511892361111109 -0.149939236111111 21 3.14 3.35389756944444 3.405 -0.0511024305555559 -0.213897569444443 22 3.3 3.39264756944444 3.4175 -0.0248524305555553 -0.092647569444444 23 3.49 3.36796006944444 3.4575 -0.0895399305555552 0.122039930555556 24 3.39 3.33441840277778 3.51416666666667 -0.179748263888889 0.0555815972222229 25 3.37 3.44702256944444 3.57666666666667 -0.129644097222222 -0.0770225694444449 26 3.54 3.53879340277778 3.63291666666667 -0.094123263888889 0.00120659722222216 27 3.7 3.64493923611111 3.68541666666667 -0.0404774305555556 0.0550607638888887 28 3.96 3.79691840277778 3.73458333333333 0.0623350694444442 0.163081597222222 29 4.03 3.86098090277778 3.76791666666667 0.0930642361111113 0.169019097222223 30 4.02 3.99618923611111 3.79708333333333 0.199105902777778 0.0238107638888887 31 4.04 4.04754340277778 3.84375 0.203793402777778 -0.00754340277777787 32 3.92 3.94743923611111 3.89625 0.0511892361111109 -0.0274392361111113 33 3.79 3.88181423611111 3.93291666666667 -0.0511024305555559 -0.0918142361111105 34 3.83 3.93181423611111 3.95666666666667 -0.0248524305555553 -0.101814236111112 35 3.76 3.89087673611111 3.98041666666667 -0.0895399305555552 -0.130876736111112 36 3.82 3.83941840277778 4.01916666666667 -0.179748263888889 -0.0194184027777782 37 4.06 3.93952256944444 4.06916666666667 -0.129644097222222 0.120477430555555 38 4.11 4.02087673611111 4.115 -0.094123263888889 0.0891232638888892 39 4.01 4.12118923611111 4.16166666666667 -0.0404774305555556 -0.111189236111111 40 4.22 4.27358506944444 4.21125 0.0623350694444442 -0.0535850694444431 41 4.34 4.35056423611111 4.2575 0.0930642361111113 -0.0105642361111098 42 4.64 4.50285590277778 4.30375 0.199105902777778 0.137144097222223 43 4.62 4.54004340277778 4.33625 0.203793402777778 0.0799565972222229 44 4.44 4.40035590277778 4.34916666666667 0.0511892361111109 0.0396440972222223 45 4.39 4.31223090277778 4.36333333333333 -0.0511024305555559 0.0777690972222214 46 4.42 4.35389756944444 4.37875 -0.0248524305555553 0.0661024305555564 47 4.28 4.30254340277778 4.39208333333333 -0.0895399305555552 -0.0225434027777771 48 4.41 4.22775173611111 4.4075 -0.179748263888889 0.182248263888889 49 4.25 4.29577256944444 4.42541666666667 -0.129644097222222 -0.045772569444444 50 4.23 4.34671006944444 4.44083333333333 -0.094123263888889 -0.116710069444443 51 4.23 4.41327256944444 4.45375 -0.0404774305555556 -0.183272569444443 52 4.37 4.52483506944444 4.4625 0.0623350694444442 -0.154835069444444 53 4.51 4.55639756944444 4.46333333333333 0.0930642361111113 -0.0463975694444452 54 4.84 4.63910590277778 4.44 0.199105902777778 0.200894097222222 55 4.85 4.61629340277778 4.4125 0.203793402777778 0.233706597222223 56 4.58 4.45910590277778 4.40791666666667 0.0511892361111109 0.120894097222222 57 4.56 4.34889756944444 4.4 -0.0511024305555559 0.211102430555555 58 4.46 4.34848090277778 4.37333333333333 -0.0248524305555553 0.111519097222223 59 4.26 4.24546006944444 4.335 -0.0895399305555552 0.0145399305555562 60 3.87 4.10525173611111 4.285 -0.179748263888889 -0.235251736111111 61 4.13 NA 4.21625 NA NA 62 4.24 NA 4.14375 NA NA 63 4.03 NA NA NA NA 64 3.93 NA NA NA NA 65 4.03 NA NA NA NA 66 4.12 NA NA NA NA 67 3.92 NA NA NA NA 68 3.77 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/1osgz1264003367.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/1osgz1264003367.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/2adda1264003367.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/2adda1264003367.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/37uwg1264003367.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/37uwg1264003367.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/4tbne1264003367.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jan/20/t1264004826bikixoxfea2ir0q/4tbne1264003367.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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