Quinten Bollaerts - Bier - Multi

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

Title produced by software: Classical Decomposition

Date of computation: Sun, 18 May 2008 14:22:02 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j.htm/, Retrieved Sun, 18 May 2008 22:23:31 +0200

User-defined keywords:

Dataseries X:

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0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,41 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,42 0,43 0,43 0,43 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,44 0,45 0,45 0,46 0,46 0,46 0,46 0,46 0,46 0,46 0,46 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47 0,47

Text written by user:

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 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 0.41 NA NA -0.00030381944444447 NA 2 0.41 NA NA -0.00134548611111113 NA 3 0.41 NA NA 0.000112847222222206 NA 4 0.41 NA NA 0.00157118055555553 NA 5 0.41 NA NA 0.000529513888888869 NA 6 0.41 NA NA 0.00198784722222224 NA 7 0.41 0.410946180555556 0.41 0.000946180555555559 -0.000946180555555676 8 0.41 0.409800347222222 0.41 -0.000199652777777773 0.000199652777777670 9 0.41 0.408550347222222 0.41 -0.00144965277777776 0.00144965277777764 10 0.41 0.409800347222222 0.41 -0.000199652777777745 0.000199652777777615 11 0.41 0.408550347222222 0.41 -0.00144965277777777 0.00144965277777764 12 0.41 0.409800347222222 0.41 -0.000199652777777745 0.000199652777777615 13 0.41 0.409696180555556 0.41 -0.00030381944444447 0.000303819444444353 14 0.41 0.408654513888889 0.41 -0.00134548611111113 0.00134548611111102 15 0.41 0.410112847222222 0.41 0.000112847222222206 -0.000112847222222323 16 0.41 0.411987847222222 0.410416666666667 0.00157118055555553 -0.00198784722222234 17 0.41 0.411779513888889 0.41125 0.000529513888888869 -0.00177951388888897 18 0.41 0.414071180555556 0.412083333333333 0.00198784722222224 -0.00407118055555566 19 0.41 0.413862847222222 0.412916666666667 0.000946180555555559 -0.00386284722222235 20 0.41 0.413550347222222 0.41375 -0.000199652777777773 -0.00355034722222231 21 0.41 0.413133680555556 0.414583333333333 -0.00144965277777776 -0.00313368055555568 22 0.42 0.415217013888889 0.415416666666667 -0.000199652777777745 0.004782986111111 23 0.42 0.414800347222222 0.41625 -0.00144965277777777 0.00519965277777767 24 0.42 0.416883680555556 0.417083333333333 -0.000199652777777745 0.00311631944444435 25 0.42 0.417612847222222 0.417916666666667 -0.00030381944444447 0.00238715277777779 26 0.42 0.417404513888889 0.41875 -0.00134548611111113 0.00259548611111116 27 0.42 0.419696180555555 0.419583333333333 0.000112847222222206 0.000303819444444520 28 0.42 0.421571180555555 0.42 0.00157118055555553 -0.00157118055555550 29 0.42 0.420529513888889 0.42 0.000529513888888869 -0.000529513888888833 30 0.42 0.422404513888889 0.420416666666667 0.00198784722222224 -0.00240451388888879 31 0.42 0.422196180555555 0.42125 0.000946180555555559 -0.00219618055555548 32 0.42 0.421883680555555 0.422083333333333 -0.000199652777777773 -0.00188368055555549 33 0.42 0.421883680555555 0.423333333333333 -0.00144965277777776 -0.00188368055555549 34 0.42 0.424800347222222 0.425 -0.000199652777777745 -0.00480034722222217 35 0.42 0.425217013888889 0.426666666666667 -0.00144965277777777 -0.00521701388888884 36 0.43 0.428133680555556 0.428333333333333 -0.000199652777777745 0.00186631944444449 37 0.43 0.429696180555555 0.43 -0.00030381944444447 0.000303819444444520 38 0.43 0.430321180555556 0.431666666666667 -0.00134548611111113 -0.000321180555555522 39 0.44 0.433446180555556 0.433333333333333 0.000112847222222206 0.00655381944444444 40 0.44 0.436571180555556 0.435 0.00157118055555553 0.0034288194444444 41 0.44 0.437196180555556 0.436666666666667 0.000529513888888869 0.00280381944444436 42 0.44 0.439904513888889 0.437916666666667 0.00198784722222224 9.54861111110428e-05 43 0.44 0.439696180555556 0.43875 0.000946180555555559 0.000303819444444353 44 0.44 0.439383680555556 0.439583333333333 -0.000199652777777773 0.000616319444444346 45 0.44 0.438550347222222 0.44 -0.00144965277777776 0.00144965277777764 46 0.44 0.440217013888889 0.440416666666667 -0.000199652777777745 -0.000217013888889006 47 0.44 0.439800347222222 0.44125 -0.00144965277777777 0.000199652777777670 48 0.44 0.442300347222222 0.4425 -0.000199652777777745 -0.00230034722222233 49 0.44 0.443862847222222 0.444166666666667 -0.00030381944444447 -0.0038628472222223 50 0.44 0.444487847222222 0.445833333333333 -0.00134548611111113 -0.00448784722222229 51 0.44 0.447612847222222 0.4475 0.000112847222222206 -0.00761284722222227 52 0.45 0.450737847222222 0.449166666666667 0.00157118055555553 -0.000737847222222254 53 0.45 0.451362847222222 0.450833333333333 0.000529513888888869 -0.00136284722222224 54 0.46 0.454487847222222 0.4525 0.00198784722222224 0.00551215277777783 55 0.46 0.455112847222222 0.454166666666667 0.000946180555555559 0.00488715277777785 56 0.46 0.456050347222222 0.45625 -0.000199652777777773 0.00394965277777787 57 0.46 0.457300347222222 0.45875 -0.00144965277777776 0.00269965277777789 58 0.46 0.460633680555556 0.460833333333333 -0.000199652777777745 -0.000633680555555516 59 0.46 0.461050347222222 0.4625 -0.00144965277777777 -0.00105034722222219 60 0.46 0.463550347222222 0.46375 -0.000199652777777745 -0.00355034722222219 61 0.46 0.464279513888889 0.464583333333333 -0.00030381944444447 -0.00427951388888875 62 0.47 0.464071180555555 0.465416666666667 -0.00134548611111113 0.00592881944444451 63 0.47 0.466362847222222 0.46625 0.000112847222222206 0.00363715277777782 64 0.47 0.468654513888889 0.467083333333333 0.00157118055555553 0.00134548611111113 65 0.47 0.468446180555556 0.467916666666667 0.000529513888888869 0.00155381944444444 66 0.47 0.470737847222222 0.46875 0.00198784722222224 -0.000737847222222254 67 0.47 NA NA 0.000946180555555559 NA 68 0.47 NA NA -0.000199652777777773 NA 69 0.47 NA NA -0.00144965277777776 NA 70 0.47 NA NA -0.000199652777777745 NA 71 0.47 NA NA -0.00144965277777777 NA 72 0.47 NA NA -0.000199652777777745 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/1bx9b1211142119.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/1bx9b1211142119.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/294bk1211142119.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/294bk1211142119.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/32xi11211142119.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/32xi11211142119.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/4lhfh1211142119.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2008/May/18/t1211142206g1ie0wislsevu2j/4lhfh1211142119.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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