ws 8

*The author of this computation has been verified*

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 12 Dec 2010 19:09:25 +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/Dec/12/t129218086781a0fbfzrpc39by.htm/, Retrieved Sun, 12 Dec 2010 20:07:47 +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/Dec/12/t129218086781a0fbfzrpc39by.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:

Dataseries X:

» Textbox « » Textfile « » CSV «

1.3031 1.3241 1.2961 1.2865 1.2305 1.2101 1.2125 1.2350 1.2014 1.1992 1.1791 1.1832 1.2159 1.1922 1.2114 1.2614 1.2812 1.2786 1.2772 1.2815 1.2679 1.2765 1.3247 1.3191 1.3029 1.3234 1.3354 1.3651 1.3453 1.3534 1.3706 1.3638 1.4268 1.4485 1.4635 1.4587 1.4876 1.5189 1.5783 1.5633 1.5554 1.5757 1.5593 1.4660 1.4065 1.2759 1.2705 1.3954 1.2793 1.2694 1.3282 1.3230 1.4135 1.4042 1.4253 1.4322 1.4632 1.4713 1.5016 1.4318

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 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 1.3031 NA NA -0.0232435763888889 NA 2 1.3241 NA NA -0.0229644097222223 NA 3 1.2961 NA NA 0.00960434027777772 NA 4 1.2865 NA NA 0.0189178819444445 NA 5 1.2305 NA NA 0.0333741319444444 NA 6 1.2101 NA NA 0.0315501736111112 NA 7 1.2125 1.25511267361111 1.23476666666667 0.0203460069444443 -0.0426126736111114 8 1.235 1.22847621527778 1.2256375 0.00283871527777778 0.00652378472222237 9 1.2014 1.20876163194444 1.2166125 -0.00785086805555547 -0.0073616319444445 10 1.1992 1.17784704861111 1.2120375 -0.0341904513888888 0.0213529513888888 11 1.1791 1.18605225694444 1.21310416666667 -0.0270519097222222 -0.00695225694444446 12 1.1832 1.21674079861111 1.21807083333333 -0.00133003472222216 -0.0335407986111109 13 1.2159 1.20037725694444 1.22362083333333 -0.0232435763888889 0.0155227430555556 14 1.1922 1.20528975694444 1.22825416666667 -0.0229644097222223 -0.0130897569444444 15 1.2114 1.24256684027778 1.2329625 0.00960434027777772 -0.0311668402777778 16 1.2614 1.25787204861111 1.23895416666667 0.0189178819444445 0.00352795138888906 17 1.2812 1.28161579861111 1.24824166666667 0.0333741319444444 -0.000415798611111073 18 1.2786 1.29152100694444 1.25997083333333 0.0315501736111112 -0.0129210069444445 19 1.2772 1.28960434027778 1.26925833333333 0.0203460069444443 -0.0124043402777780 20 1.2815 1.28118871527778 1.27835 0.00283871527777778 0.000311284722222194 21 1.2679 1.28113246527778 1.28898333333333 -0.00785086805555547 -0.0132324652777778 22 1.2765 1.26428038194444 1.29847083333333 -0.0341904513888888 0.0122196180555558 23 1.3247 1.27841059027778 1.3054625 -0.0270519097222222 0.0462894097222224 24 1.3191 1.30991996527778 1.31125 -0.00133003472222216 0.0091800347222224 25 1.3029 1.29501475694444 1.31825833333333 -0.0232435763888889 0.00788524305555582 26 1.3234 1.30261475694444 1.32557916666667 -0.0229644097222223 0.0207852430555555 27 1.3354 1.34523350694444 1.33562916666667 0.00960434027777772 -0.0098335069444444 28 1.3651 1.36833454861111 1.34941666666667 0.0189178819444445 -0.00323454861111094 29 1.3453 1.39574079861111 1.36236666666667 0.0333741319444444 -0.0504407986111113 30 1.3534 1.40551684027778 1.37396666666667 0.0315501736111112 -0.0521168402777781 31 1.3706 1.40782517361111 1.38747916666667 0.0203460069444443 -0.0372251736111111 32 1.3638 1.40615954861111 1.40332083333333 0.00283871527777778 -0.0423595486111112 33 1.4268 1.41373663194444 1.4215875 -0.00785086805555547 0.0130633680555559 34 1.4485 1.40577621527778 1.43996666666667 -0.0341904513888888 0.0427237847222226 35 1.4635 1.42992725694444 1.45697916666667 -0.0270519097222222 0.0335727430555557 36 1.4587 1.47366579861111 1.47499583333333 -0.00133003472222216 -0.0149657986111109 37 1.4876 1.46887725694444 1.49212083333333 -0.0232435763888889 0.0187227430555557 38 1.5189 1.48127725694444 1.50424166666667 -0.0229644097222223 0.0376227430555556 39 1.5783 1.51725850694444 1.50765416666667 0.00960434027777772 0.0610414930555556 40 1.5633 1.51853454861111 1.49961666666667 0.0189178819444445 0.0447654513888889 41 1.5554 1.51775746527778 1.48438333333333 0.0333741319444444 0.0376425347222222 42 1.5757 1.50525434027778 1.47370416666667 0.0315501736111112 0.0704456597222227 43 1.5593 1.48273350694444 1.4623875 0.0203460069444443 0.076566493055556 44 1.466 1.44615121527778 1.4433125 0.00283871527777778 0.0198487847222224 45 1.4065 1.41464496527778 1.42249583333333 -0.00785086805555547 -0.00814496527777742 46 1.2759 1.36787204861111 1.4020625 -0.0341904513888888 -0.0919720486111113 47 1.2705 1.35908559027778 1.3861375 -0.0270519097222222 -0.0885855902777779 48 1.3954 1.37174913194444 1.37307916666667 -0.00133003472222216 0.0236508680555556 49 1.2793 1.33710642361111 1.36035 -0.0232435763888889 -0.0578064236111111 50 1.2694 1.33039392361111 1.35335833333333 -0.0229644097222223 -0.0609939236111108 51 1.3282 1.36391684027778 1.3543125 0.00960434027777772 -0.0357168402777774 52 1.323 1.38373454861111 1.36481666666667 0.0189178819444445 -0.060734548611111 53 1.4135 1.41596163194444 1.3825875 0.0333741319444444 -0.00246163194444438 54 1.4042 1.42528350694444 1.39373333333333 0.0315501736111112 -0.0210835069444446 55 1.4253 NA NA 0.0203460069444443 NA 56 1.4322 NA NA 0.00283871527777778 NA 57 1.4632 NA NA -0.00785086805555547 NA 58 1.4713 NA NA -0.0341904513888888 NA 59 1.5016 NA NA -0.0270519097222222 NA 60 1.4318 NA NA -0.00133003472222216 NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/1frw91292180962.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/1frw91292180962.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/2frw91292180962.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/2frw91292180962.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/3q0vb1292180962.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/3q0vb1292180962.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/4q0vb1292180962.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/12/t129218086781a0fbfzrpc39by/4q0vb1292180962.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 1 ;

Parameters (R input):

par1 = additive ; par2 = 12 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ; par8 = 1 ;

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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