Classical Decomposition - gemiddelde prijs strip - Kenny Dellaert

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Fri, 29 May 2009 05:31:54 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6.htm/, Retrieved Fri, 29 May 2009 13:35:27 +0200

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/2009/May/29/t1243596922gvssfhkqr4nrup6.htm/}, year = {2009}, } @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 = {2009}, 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:

Dataseries X:

» Textbox « » Textfile « » CSV «

5,11 5,11 5,11 5,1 5,1 5,1 5,1 5,1 5,12 5,25 5,26 5,26 5,26 5,26 5,26 5,26 5,29 5,3 5,33 5,33 5,35 5,38 5,38 5,38 5,38 5,38 5,39 5,39 5,4 5,4 5,4 5,4 5,4 5,41 5,41 5,41 5,41 5,41 5,42 5,42 5,42 5,42 5,43 5,43 5,45 5,51 5,51 5,51 5,51 5,51 5,51 5,53 5,53 5,53 5,53 5,52 5,53 5,54 5,54 5,57 5,56 5,57 5,58 5,61 5,66 5,68 5,69 5,7 5,72 5,71 5,69 5,7 5,7

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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 5.11 NA NA 1.00069597627142 NA 2 5.11 NA NA 0.99921889698968 NA 3 5.11 NA NA 0.998475750820238 NA 4 5.1 NA NA 0.99865084599588 NA 5 5.1 NA NA 1.00057505922897 NA 6 5.1 NA NA 1.00033487139641 NA 7 5.1 5.15393549342138 5.14958333333333 1.00084514800642 0.989535085666046 8 5.1 5.14462589254435 5.16208333333333 0.996618140455763 0.991325726403347 9 5.12 5.15913503514901 5.17458333333333 0.997014581235013 0.992414419300448 10 5.25 5.18920296952037 5.1875 1.00032828328103 1.01171606330235 11 5.26 5.22156465408595 5.20208333333333 1.00374490747347 1.00736088671888 12 5.26 5.23658465687652 5.21833333333333 1.00349753884571 1.00447149137420 13 5.26 5.23989430575121 5.23625 1.00069597627142 1.00383704194696 14 5.26 5.25131164488785 5.25541666666667 0.99921889698968 1.00165451142490 15 5.26 5.26654355401391 5.27458333333333 0.998475750820238 0.998757523991437 16 5.26 5.28244687079904 5.28958333333333 0.99865084599588 0.995750667948384 17 5.29 5.30304781391355 5.3 1.00057505922897 0.997539563215078 18 5.3 5.31177816711491 5.31 1.00033487139641 0.99778263196535 19 5.33 5.32449618739414 5.32 1.00084514800642 1.00103367763111 20 5.33 5.31197468862922 5.33 0.996618140455763 1.00339333532770 21 5.35 5.32447328653715 5.34041666666667 0.997014581235013 1.00479422321967 22 5.38 5.35300672590763 5.35125 1.00032828328103 1.0050426378061 23 5.38 5.38132738519214 5.36125 1.00374490747347 0.999753334986495 24 5.38 5.38878178360145 5.37 1.00349753884571 0.998370358282427 25 5.38 5.38082565574277 5.37708333333333 1.00069597627142 0.999846555938514 26 5.38 5.37871205425403 5.38291666666667 0.99921889698968 1.00023945244382 27 5.39 5.37970413910687 5.38791666666667 0.998475750820238 1.00191383403750 28 5.39 5.38397637347529 5.39125 0.99865084599588 1.00111880627010 29 5.4 5.39685172571627 5.39375 1.00057505922897 1.00058335385957 30 5.4 5.39805704977285 5.39625 1.00033487139641 1.00035993510429 31 5.4 5.40331274279964 5.39875 1.00084514800642 0.999386905226972 32 5.4 5.38298373113669 5.40125 0.996618140455763 1.00316112210499 33 5.4 5.3876175433487 5.40375 0.997014581235013 1.00229831767969 34 5.41 5.40802478148809 5.40625 1.00032828328103 1.00036523843579 35 5.41 5.42858704125235 5.40833333333333 1.00374490747347 0.99657608119551 36 5.41 5.42892168515528 5.41 1.00349753884571 0.996514651296772 37 5.41 5.41585001491227 5.41208333333333 1.00069597627142 0.998919834394203 38 5.41 5.41035398599204 5.41458333333333 0.99921889698968 0.999934572489535 39 5.42 5.40965841163148 5.41791666666667 0.998475750820238 1.00191168971894 40 5.42 5.41684863048932 5.42416666666667 0.99865084599588 1.00058177175063 41 5.42 5.4356240092614 5.4325 1.00057505922897 0.997125627299686 42 5.42 5.44265531278928 5.44083333333333 1.00033487139641 0.995837452220051 43 5.43 5.45377201901163 5.44916666666667 1.00084514800642 0.99564117844883 44 5.43 5.43904350153733 5.4575 0.996618140455763 0.998337299281616 45 5.45 5.44910010919152 5.46541666666667 0.997014581235013 1.00016514484785 46 5.51 5.47554694060956 5.47375 1.00032828328103 1.00629216766181 47 5.51 5.50344968226808 5.48291666666667 1.00374490747347 1.00119022033635 48 5.51 5.51129210813553 5.49208333333333 1.00349753884571 0.999765552594531 49 5.51 5.50466178280635 5.50083333333333 1.00069597627142 1.00096976297623 50 5.51 5.5044470987919 5.50875 0.99921889698968 1.00100880272050 51 5.51 5.5074258288993 5.51583333333333 0.998475750820238 1.00046740004871 52 5.53 5.51296877441643 5.52041666666667 0.99865084599588 1.00308930202228 53 5.53 5.52609267086668 5.52291666666667 1.00057505922897 1.00070706905693 54 5.53 5.5285173892508 5.52666666666667 1.00033487139641 1.00026817510823 55 5.53 5.53592472491049 5.53125 1.00084514800642 0.99892976779763 56 5.52 5.5171119225397 5.53583333333333 0.996618140455763 1.00052347632255 57 5.53 5.52470704826852 5.54125 0.997014581235013 1.00095805111208 58 5.54 5.54932115150154 5.5475 1.00032828328103 0.998320307791338 59 5.54 5.57705764214947 5.55625 1.00374490747347 0.993355341736222 60 5.57 5.587390671498 5.56791666666667 1.00349753884571 0.996887514670003 61 5.56 5.58471746090807 5.58083333333333 1.00069597627142 0.995574089274688 62 5.57 5.59062972865726 5.595 0.99921889698968 0.99630994545185 63 5.58 5.60186499366438 5.61041666666667 0.998475750820238 0.996096836733997 64 5.61 5.61782711324599 5.62541666666667 0.99865084599588 0.998606736539197 65 5.66 5.64199261522737 5.63875 1.00057505922897 1.00319167109933 66 5.68 5.6523088295861 5.65041666666667 1.00033487139641 1.00489909013268 67 5.69 5.666451612963 5.66166666666667 1.00084514800642 1.00415575542605 68 5.7 NA NA 0.996618140455763 NA 69 5.72 NA NA 0.997014581235013 NA 70 5.71 NA NA 1.00032828328103 NA 71 5.69 NA NA 1.00374490747347 NA 72 5.7 NA NA 1.00349753884571 NA 73 5.7 NA NA NA NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/1b4x31243596712.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/1b4x31243596712.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/2r6ed1243596712.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/2r6ed1243596712.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/3mn5l1243596712.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/3mn5l1243596712.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/4aklp1243596712.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/May/29/t1243596922gvssfhkqr4nrup6/4aklp1243596712.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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