decompositie eigen tijdreeks wijnprijzen 2000-2005

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Sat, 29 May 2010 12:35:13 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x.htm/, Retrieved Sat, 29 May 2010 14:37:22 +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/2010/May/29/t1275136641qgqh2i9evh2kc4x.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 «

2,17 2,18 2,18 2,18 2,17 2,17 2,18 2,17 2,18 2,17 2,17 2,17 2,17 2,17 2,17 2,17 2,17 2,17 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,18 2,19 2,19 2,19 2,20 2,20 2,21 2,21 2,21 2,20 2,21 2,20 2,21 2,21 2,22 2,22 2,23 2,24 2,24 2,25 2,25 2,32 2,36 2,37 2,37 2,37 2,38 2,38 2,41 2,42 2,43 2,44 2,44 2,44 2,43 2,43 2,43 2,42 2,42 2,42 2,42 2,42

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 3 seconds R Server 'RServer@AstonUniversity' @ vre.aston.ac.uk Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 2.17 NA NA 0.999604207607484 NA 2 2.18 NA NA 0.999504423159968 NA 3 2.18 NA NA 0.99774038265317 NA 4 2.18 NA NA 1.00115055499094 NA 5 2.17 NA NA 1.00286184124549 NA 6 2.17 NA NA 1.00098135176417 NA 7 2.18 2.17708853348329 2.17416666666667 1.00134390194709 1.00133732113873 8 2.17 2.17257766508782 2.17375 0.99946068549181 0.998813545251228 9 2.18 2.1734877936681 2.17291666666667 1.00026283888848 1.00299620101428 10 2.17 2.16660545689082 2.17208333333333 0.99747805419873 1.00156675646615 11 2.17 2.17143825430203 2.17166666666667 0.999894821627951 0.999337648998683 12 2.17 2.17105194693569 2.17166666666667 0.999716936424723 0.999515466713187 13 2.17 2.17080713752092 2.17166666666667 0.999604207607484 0.99962818552281 14 2.17 2.17100689913871 2.17208333333333 0.999504423159968 0.999536206384644 15 2.17 2.16759098131401 2.1725 0.99774038265317 1.00111138065565 16 2.17 2.17541672678239 2.17291666666667 1.00115055499094 0.997510027979602 17 2.17 2.17997092740739 2.17375 1.00286184124549 0.995426119090843 18 2.17 2.17671736452383 2.17458333333333 1.00098135176417 0.996913993229756 19 2.18 2.17834021336072 2.17541666666667 1.00134390194709 1.00076195014401 20 2.18 2.17507631680155 2.17625 0.99946068549181 1.00226368296157 21 2.18 2.1776555554968 2.17708333333333 1.00026283888848 1.00107659106018 22 2.18 2.17242407887365 2.17791666666667 0.99747805419873 1.003487312261 23 2.18 2.1785208426219 2.17875 0.999894821627951 1.00067897325064 24 2.18 2.17896637268239 2.17958333333333 0.999716936424723 1.00047436588769 25 2.18 2.17913717258432 2.18 0.999604207607484 1.00039594910616 26 2.18 2.17933610266505 2.18041666666667 0.999504423159968 1.00030463283481 27 2.18 2.17632120966223 2.18125 0.99774038265317 1.00169037103597 28 2.18 2.18459394020314 2.18208333333333 1.00115055499094 0.997897119405762 29 2.18 2.18958168671932 2.18333333333333 1.00286184124549 0.995623964715526 30 2.18 2.18714425360471 2.185 1.00098135176417 0.996733524278095 31 2.18 2.19002255888344 2.18708333333333 1.00134390194709 0.995423536235833 32 2.19 2.18840245927477 2.18958333333333 0.99946068549181 1.00073000316667 33 2.19 2.19265949808013 2.19208333333333 1.00026283888848 0.998787090251608 34 2.19 2.18863309725438 2.19416666666667 0.99747805419873 1.0006245463195 35 2.2 2.19601900200039 2.19625 0.999894821627951 1.00181282493275 36 2.2 2.19771106524035 2.19833333333333 0.999716936424723 1.00104150850212 37 2.21 2.19954575848963 2.20041666666667 0.999604207607484 1.00475290930867 38 2.21 2.20140849200983 2.2025 0.999504423159968 1.00390273228315 39 2.21 2.1996018185908 2.20458333333333 0.99774038265317 1.00472730169675 40 2.2 2.20962270407792 2.20708333333333 1.00115055499094 0.995645091779625 41 2.21 2.21590681005202 2.20958333333333 1.00286184124549 0.997334359899423 42 2.2 2.21467124077822 2.2125 1.00098135176417 0.993375431753444 43 2.21 2.21839396943861 2.21541666666667 1.00134390194709 0.996216195340303 44 2.21 2.21713695398266 2.21833333333333 0.99946068549181 0.996781004452683 45 2.22 2.22225060706391 2.22166666666667 1.00026283888848 0.99898723975741 46 2.22 2.2227135974395 2.22833333333333 0.99747805419873 0.998779151104925 47 2.23 2.23934777760427 2.23958333333333 0.999894821627951 0.995825669555326 48 2.24 2.2522789480202 2.25291666666667 0.999716936424723 0.994548211698648 49 2.24 2.26576953724363 2.26666666666667 0.999604207607484 0.988626584999029 50 2.25 2.27887008480473 2.28 0.999504423159968 0.987331403840338 51 2.25 2.28815127755127 2.29333333333333 0.99774038265317 0.983326592989909 52 2.32 2.30932061351243 2.30666666666667 1.00115055499094 1.00462447112154 53 2.36 2.32747518989058 2.32083333333333 1.00286184124549 1.01397428864148 54 2.37 2.3381256074958 2.33583333333333 1.00098135176417 1.01363245516067 55 2.37 2.35440984945309 2.35125 1.00134390194709 1.00662168082186 56 2.37 2.36580673094957 2.36708333333333 0.99946068549181 1.00177244784858 57 2.38 2.38354298983468 2.38291666666667 1.00026283888848 0.998513561597258 58 2.38 2.38979117151779 2.39583333333333 0.99747805419873 0.995902917529161 59 2.41 2.40349717748819 2.40375 0.999894821627951 1.00270556694334 60 2.42 2.40848471933656 2.40916666666667 0.999716936424723 1.00478113087909 61 2.43 2.41321115786573 2.41416666666667 0.999604207607484 1.00695705474407 62 2.44 2.41755132351817 2.41875 0.999504423159968 1.00928570833779 63 2.44 2.41702607697731 2.4225 0.99774038265317 1.00950503730246 64 2.44 2.42862438798218 2.42583333333333 1.00115055499094 1.0046839733942 65 2.43 2.43486497872395 2.42791666666667 1.00286184124549 0.998001951333458 66 2.43 2.43071638253399 2.42833333333333 1.00098135176417 0.999705279258768 67 2.43 NA NA 1.00134390194709 NA 68 2.42 NA NA 0.99946068549181 NA 69 2.42 NA NA 1.00026283888848 NA 70 2.42 NA NA 0.99747805419873 NA 71 2.42 NA NA 0.999894821627951 NA 72 2.42 NA NA 0.999716936424723 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/1iix31275136509.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/1iix31275136509.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/2iix31275136509.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/2iix31275136509.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/3t9w61275136509.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/3t9w61275136509.ps (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/4t9w61275136509.png (open in new window) http://www.freestatistics.org/blog/date/2010/May/29/t1275136641qgqh2i9evh2kc4x/4t9w61275136509.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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