Wisselkoersen

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Tue, 01 Jun 2010 20:44:47 +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/Jun/01/t1275425139bljdib07oqxpui4.htm/, Retrieved Tue, 01 Jun 2010 22:45:44 +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/Jun/01/t1275425139bljdib07oqxpui4.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 «

1.4272 1.4614 1.4914 1.4816 1.4562 1.4268 1.4088 1.4016 1.365 1.319 1.305 1.2785 1.3239 1.3449 1.2732 1.3322 1.4369 1.4975 1.577 1.5553 1.5557 1.575 1.5527 1.4748 1.4718 1.457 1.4684 1.4227 1.3896 1.3622 1.3716 1.3419 1.3511 1.3516 1.3242 1.3074 1.2999 1.3213 1.2881 1.2611 1.2727 1.2811 1.2684 1.265 1.277 1.2271 1.202 1.1938 1.2103 1.1856 1.1786 1.2015 1.2256 1.2292 1.2037 1.2165 1.2694 1.2938 1.3201 1.3014 1.3119 1.3408 1.2991 1.249 1.2218 1.2176 1.2266 1.2138 1.2007 1.1985 1.2262 1.2646

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.4272 NA NA -0.00418368055555557 NA 2 1.4614 NA NA 0.00525965277777782 NA 3 1.4914 NA NA -0.0202461805555554 NA 4 1.4816 NA NA -0.0260528472222221 NA 5 1.4562 NA NA -0.0083720138888889 NA 6 1.4268 NA NA 0.000600486111111157 NA 7 1.4088 1.41676298611111 1.39757083333333 0.0191921527777777 -0.00796298611111101 8 1.4016 1.39973048611111 1.3884125 0.0113179861111111 0.00186951388888912 9 1.365 1.39597215277778 1.37446666666667 0.0215054861111112 -0.030972152777778 10 1.319 1.37385631944444 1.35915 0.0147063194444444 -0.0548563194444445 11 1.305 1.35821881944444 1.35212083333333 0.00609798611111109 -0.0532188194444443 12 1.2785 1.33443715277778 1.3542625 -0.0198253472222223 -0.0559371527777777 13 1.3239 1.36003298611111 1.36421666666667 -0.00418368055555557 -0.0361329861111110 14 1.3449 1.38288881944444 1.37762916666667 0.00525965277777782 -0.0379888194444444 15 1.2732 1.37173298611111 1.39197916666667 -0.0202461805555554 -0.098532986111111 16 1.3322 1.38453881944444 1.41059166666667 -0.0260528472222221 -0.0523388194444443 17 1.4369 1.42320715277778 1.43157916666667 -0.0083720138888889 0.0136928472222224 18 1.4975 1.45067965277778 1.45007916666667 0.000600486111111157 0.0468203472222224 19 1.577 1.48361298611111 1.46442083333333 0.0191921527777777 0.093387013888889 20 1.5553 1.48657215277778 1.47525416666667 0.0113179861111111 0.0687278472222221 21 1.5557 1.50956381944444 1.48805833333333 0.0215054861111112 0.0461361805555556 22 1.575 1.51466881944444 1.4999625 0.0147063194444444 0.0603311805555558 23 1.5527 1.50786048611111 1.5017625 0.00609798611111109 0.0448395138888891 24 1.4748 1.47432881944444 1.49415416666667 -0.0198253472222223 0.000471180555555728 25 1.4718 1.47577465277778 1.47995833333333 -0.00418368055555557 -0.00397465277777753 26 1.457 1.46776798611111 1.46250833333333 0.00525965277777782 -0.0107679861111107 27 1.4684 1.42484548611111 1.44509166666667 -0.0202461805555554 0.0435545138888891 28 1.4227 1.40120548611111 1.42725833333333 -0.0260528472222221 0.0214945138888889 29 1.3896 1.40005715277778 1.40842916666667 -0.0083720138888889 -0.0104571527777777 30 1.3622 1.39253381944444 1.39193333333333 0.000600486111111157 -0.0303338194444442 31 1.3716 1.39698798611111 1.37779583333333 0.0191921527777777 -0.0253879861111113 32 1.3419 1.37629715277778 1.36497916666667 0.0113179861111111 -0.0343971527777776 33 1.3511 1.37331798611111 1.3518125 0.0215054861111112 -0.0222179861111111 34 1.3516 1.35227298611111 1.33756666666667 0.0147063194444444 -0.000672986111111218 35 1.3242 1.33206048611111 1.3259625 0.00609798611111109 -0.00786048611111112 36 1.3074 1.29788715277778 1.3177125 -0.0198253472222223 0.00951284722222212 37 1.2999 1.30584965277778 1.31003333333333 -0.00418368055555557 -0.00594965277777781 38 1.3213 1.30778881944444 1.30252916666667 0.00525965277777782 0.0135111805555554 39 1.2881 1.27599131944444 1.2962375 -0.0202461805555554 0.0121086805555555 40 1.2611 1.26190965277778 1.2879625 -0.0260528472222221 -0.00080965277777767 41 1.2727 1.26931131944444 1.27768333333333 -0.0083720138888889 0.00338868055555563 42 1.2811 1.26845881944444 1.26785833333333 0.000600486111111157 0.0126411805555555 43 1.2684 1.27858381944444 1.25939166666667 0.0191921527777777 -0.0101838194444444 44 1.265 1.26132215277778 1.25000416666667 0.0113179861111111 0.00367784722222231 45 1.277 1.26129298611111 1.2397875 0.0215054861111112 0.0157070138888888 46 1.2271 1.24744798611111 1.23274166666667 0.0147063194444444 -0.0203479861111111 47 1.202 1.23439381944444 1.22829583333333 0.00609798611111109 -0.0323938194444442 48 1.1938 1.20434548611111 1.22417083333333 -0.0198253472222223 -0.0105454861111112 49 1.2103 1.21512881944444 1.2193125 -0.00418368055555557 -0.00482881944444458 50 1.1856 1.21985548611111 1.21459583333333 0.00525965277777782 -0.0342554861111108 51 1.1786 1.19201215277778 1.21225833333333 -0.0202461805555554 -0.0134121527777780 52 1.2015 1.18866798611111 1.21472083333333 -0.0260528472222221 0.0128320138888887 53 1.2256 1.21404881944444 1.22242083333333 -0.0083720138888889 0.0115511805555557 54 1.2292 1.23242548611111 1.231825 0.000600486111111157 -0.00322548611111095 55 1.2037 1.25973381944444 1.24054166666667 0.0191921527777777 -0.0560338194444443 56 1.2165 1.26255965277778 1.25124166666667 0.0113179861111111 -0.0460596527777777 57 1.2694 1.28423465277778 1.26272916666667 0.0215054861111112 -0.0148346527777778 58 1.2938 1.28443548611111 1.26972916666667 0.0147063194444444 0.00936451388888915 59 1.3201 1.27764798611111 1.27155 0.00609798611111109 0.0424520138888889 60 1.3014 1.25108298611111 1.27090833333333 -0.0198253472222223 0.0503170138888887 61 1.3119 1.26719548611111 1.27137916666667 -0.00418368055555557 0.0447045138888886 62 1.3408 1.27748048611111 1.27222083333333 0.00525965277777782 0.0633195138888889 63 1.2991 1.24899965277778 1.26924583333333 -0.0202461805555554 0.0501003472222221 64 1.249 1.23635965277778 1.2624125 -0.0260528472222221 0.0126403472222223 65 1.2218 1.24615715277778 1.25452916666667 -0.0083720138888889 -0.0243571527777777 66 1.2176 1.24968381944444 1.24908333333333 0.000600486111111157 -0.0320838194444444 67 1.2266 NA NA 0.0191921527777777 NA 68 1.2138 NA NA 0.0113179861111111 NA 69 1.2007 NA NA 0.0215054861111112 NA 70 1.1985 NA NA 0.0147063194444444 NA 71 1.2262 NA NA 0.00609798611111109 NA 72 1.2646 NA NA -0.0198253472222223 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/1fr4c1275425084.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/1fr4c1275425084.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/2fr4c1275425084.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/2fr4c1275425084.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/3fr4c1275425084.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/3fr4c1275425084.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/4803f1275425084.png (open in new window) http://www.freestatistics.org/blog/date/2010/Jun/01/t1275425139bljdib07oqxpui4/4803f1275425084.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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