Classical decomposition - King size sigarets - Vincent Bruyninckx

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sat, 06 Jun 2009 05:39:03 -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/Jun/06/t1244288390ydkbpqfvebva69l.htm/, Retrieved Sat, 06 Jun 2009 13:39:55 +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/Jun/06/t1244288390ydkbpqfvebva69l.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 «

2,98 2,98 2,98 3,03 3,07 3,08 3,08 3,08 3,08 3,08 3,08 3,08 3,08 3,08 3,12 3,15 3,15 3,15 3,15 3,16 3,19 3,2 3,2 3,2 3,21 3,21 3,21 3,21 3,21 3,28 3,3 3,3 3,3 3,3 3,3 3,3 3,3 3,45 3,49 3,5 3,54 3,64 3,67 3,67 3,68 3,68 3,68 3,68 3,7 3,83 3,87 3,87 3,87 3,87 3,87 3,87 3,87 3,87 3,87 3,88 3,88 3,88 3,88 3,88 3,88 3,89 3,89 3,91 3,95 3,99 3,99 3,99

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 2.98 NA NA 0.989036721983282 NA 2 2.98 NA NA 1.00075659555749 NA 3 2.98 NA NA 1.00365853400266 NA 4 3.03 NA NA 1.00190572192095 NA 5 3.07 NA NA 0.999877824940684 NA 6 3.08 NA NA 1.00603355088746 NA 7 3.08 3.07851249313886 3.05416666666667 1.00797134836743 1.00048319013304 8 3.08 3.07536515707968 3.0625 1.00420086761785 1.00150708702336 9 3.08 3.07927768829541 3.0725 1.00220591970559 1.00023457179823 10 3.08 3.07890185219359 3.08333333333333 0.998562762873595 1.00035666866277 11 3.08 3.07488838904425 3.09166666666667 0.994573063841804 1.00166237284383 12 3.08 3.07070793813310 3.09791666666667 0.9912170883012 1.00302603245053 13 3.08 3.06972272585561 3.10375 0.989036721983282 1.00334794867883 14 3.08 3.11235301218379 3.11 1.00075659555749 0.989604967027476 15 3.12 3.12932367080914 3.11791666666667 1.00365853400266 0.997020547635864 16 3.15 3.13346014530778 3.1275 1.00190572192095 1.00527846339995 17 3.15 3.13711667575140 3.1375 0.999877824940684 1.00410674054561 18 3.15 3.16649060141828 3.1475 1.00603355088746 0.994792152103376 19 3.15 3.18308952053198 3.15791666666667 1.00797134836743 0.98960459003162 20 3.16 3.18206149926407 3.16875 1.00420086761785 0.993066916126802 21 3.19 3.18492689566437 3.17791666666667 1.00220591970559 1.00159284796851 22 3.2 3.17959026411667 3.18416666666667 0.998562762873595 1.00641898300975 23 3.2 3.17185926276882 3.18916666666667 0.994573063841804 1.00887200058385 24 3.2 3.16900363272296 3.19708333333333 0.9912170883012 1.00978110815556 25 3.21 3.17357158166386 3.20875 0.989036721983282 1.01147868179392 26 3.21 3.22327020152474 3.22083333333333 1.00075659555749 0.995883000587893 27 3.21 3.24307163799611 3.23125 1.00365853400266 0.989802372044873 28 3.21 3.24617453902389 3.24 1.00190572192095 0.988856255697587 29 3.21 3.24793646801566 3.24833333333333 0.999877824940684 0.98831982448264 30 3.28 3.27631593072349 3.25666666666667 1.00603355088746 1.00112445483110 31 3.3 3.29060646435784 3.26458333333333 1.00797134836743 1.00285465179258 32 3.3 3.29210517767386 3.27833333333333 1.00420086761785 1.00239810756341 33 3.3 3.30727953502843 3.3 1.00220591970559 0.997798935665603 34 3.3 3.31897298310111 3.32375 0.998562762873595 0.994283477690926 35 3.3 3.33140535842678 3.34958333333333 0.994573063841804 0.99057293993139 36 3.3 3.34866172997756 3.37833333333333 0.9912170883012 0.985468305280903 37 3.3 3.37137892606051 3.40875 0.989036721983282 0.978827972878172 38 3.45 3.44218570680294 3.43958333333333 1.00075659555749 1.00227015444914 39 3.49 3.48353149510091 3.47083333333333 1.00365853400266 1.00185688141709 40 3.5 3.50917479102814 3.5025 1.00190572192095 0.997385484743708 41 3.54 3.53373487964453 3.53416666666667 0.999877824940684 1.00177294578367 42 3.64 3.58734797020620 3.56583333333333 1.00603355088746 1.01467714596719 43 3.67 3.62701690187547 3.59833333333333 1.00797134836743 1.01185081274430 44 3.67 3.64608598350915 3.63083333333333 1.00420086761785 1.00655881857943 45 3.68 3.67057918092171 3.6625 1.00220591970559 1.00256657563124 46 3.68 3.68844120536434 3.69375 0.998562762873595 0.997711443698203 47 3.68 3.70271263559438 3.72291666666667 0.994573063841804 0.99386594698815 48 3.68 3.71334701704837 3.74625 0.9912170883012 0.99101968738842 49 3.7 3.72289906099874 3.76416666666667 0.989036721983282 0.993849131920167 50 3.83 3.78369389503693 3.78083333333333 1.00075659555749 1.0122383327636 51 3.87 3.81097509181928 3.79708333333333 1.00365853400266 1.01548813801156 52 3.87 3.8201830255411 3.81291666666667 1.00190572192095 1.01304046798958 53 3.87 3.82828222224164 3.82875 0.999877824940684 1.01089725765671 54 3.87 3.86819900316228 3.845 1.00603355088746 1.00046559053354 55 3.87 3.89160938082192 3.86083333333333 1.00797134836743 0.99444718657314 56 3.87 3.88667577470927 3.87041666666667 1.00420086761785 0.995709501981674 57 3.87 3.88146000985976 3.87291666666667 1.00220591970559 0.997047500211095 58 3.87 3.86818250268159 3.87375 0.998562762873595 1.00046985821304 59 3.87 3.85355621694372 3.87458333333333 0.994573063841804 1.00426717092746 60 3.88 3.8417922314074 3.87583333333333 0.9912170883012 1.00994529799926 61 3.88 3.83498988949018 3.8775 0.989036721983282 1.0117366960036 62 3.88 3.88293559076305 3.88 1.00075659555749 0.999243976446575 63 3.88 3.89921340460035 3.885 1.00365853400266 0.995072492165297 64 3.88 3.90075294401224 3.89333333333333 1.00190572192095 0.994679759443854 65 3.88 3.9028564433518 3.90333333333333 0.999877824940684 0.994143662806062 66 3.89 3.93652544849339 3.91291666666667 1.00603355088746 0.988181087839482 67 3.89 NA NA 1.00797134836743 NA 68 3.91 NA NA 1.00420086761785 NA 69 3.95 NA NA 1.00220591970559 NA 70 3.99 NA NA 0.998562762873595 NA 71 3.99 NA NA 0.994573063841804 NA 72 3.99 NA NA 0.9912170883012 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/168r61244288340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/168r61244288340.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/2ml981244288340.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/2ml981244288340.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/3rkq51244288341.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/3rkq51244288341.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/41vw91244288341.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/06/t1244288390ydkbpqfvebva69l/41vw91244288341.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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