Inleiding kwantitatief onderzoek, opgave 9 (Bouke Van Leuffelen)

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Mon, 16 May 2011 15:13:46 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on.htm/, Retrieved Mon, 16 May 2011 17:11:03 +0200

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

KDGP2W92

Dataseries X:

» Textbox « » Textfile « » CSV «

130 127 122 117 112 113 149 157 157 147 137 132 125 123 117 114 111 112 144 150 149 134 123 116 117 111 105 102 95 93 124 130 124 115 106 105 105 101 95 93 84 87 116 120 117 109 105 107 109 109 108 107 99 103 131 137 135 124 118 121 121 118 113 107 100 102 130 136 133 120 112 109 110

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 'Herman Ole Andreas Wold' @ www.yougetit.org Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 130 NA NA -2.04097222222222 NA 2 127 NA NA -4.70763888888888 NA 3 122 NA NA -9.13263888888888 NA 4 117 NA NA -11.7076388888889 NA 5 112 NA NA -18.0743055555556 NA 6 113 NA NA -16.0743055555556 NA 7 149 146.967361111111 133.125 13.8423611111111 2.0326388888889 8 157 151.500694444444 132.75 18.7506944444444 5.49930555555557 9 157 150.475694444444 132.375 18.1006944444444 6.52430555555554 10 147 141.709027777778 132.041666666667 9.66736111111111 5.29097222222222 11 137 133.759027777778 131.875 1.88402777777778 3.24097222222221 12 132 131.284027777778 131.791666666667 -0.50763888888889 0.715972222222234 13 125 129.500694444444 131.541666666667 -2.04097222222222 -4.50069444444443 14 123 126.334027777778 131.041666666667 -4.70763888888888 -3.33402777777778 15 117 121.284027777778 130.416666666667 -9.13263888888888 -4.28402777777777 16 114 117.834027777778 129.541666666667 -11.7076388888889 -3.83402777777779 17 111 110.342361111111 128.416666666667 -18.0743055555556 0.657638888888897 18 112 111.092361111111 127.166666666667 -16.0743055555556 0.907638888888883 19 144 140.009027777778 126.166666666667 13.8423611111111 3.99097222222224 20 150 144.084027777778 125.333333333333 18.7506944444444 5.91597222222224 21 149 142.434027777778 124.333333333333 18.1006944444444 6.56597222222221 22 134 133.000694444444 123.333333333333 9.66736111111111 0.999305555555566 23 123 124.050694444444 122.166666666667 1.88402777777778 -1.05069444444445 24 116 120.200694444444 120.708333333333 -0.50763888888889 -4.20069444444445 25 117 117.042361111111 119.083333333333 -2.04097222222222 -0.04236111111112 26 111 112.709027777778 117.416666666667 -4.70763888888888 -1.70902777777779 27 105 106.409027777778 115.541666666667 -9.13263888888888 -1.40902777777778 28 102 102.000694444444 113.708333333333 -11.7076388888889 -0.000694444444420128 29 95 94.1340277777778 112.208333333333 -18.0743055555556 0.865972222222226 30 93 94.9673611111111 111.041666666667 -16.0743055555556 -1.9673611111111 31 124 123.925694444444 110.083333333333 13.8423611111111 0.0743055555555685 32 130 127.917361111111 109.166666666667 18.7506944444444 2.08263888888891 33 124 126.434027777778 108.333333333333 18.1006944444444 -2.43402777777776 34 115 117.209027777778 107.541666666667 9.66736111111111 -2.20902777777775 35 106 108.592361111111 106.708333333333 1.88402777777778 -2.59236111111109 36 105 105.492361111111 106 -0.50763888888889 -0.49236111111108 37 105 103.375694444444 105.416666666667 -2.04097222222222 1.62430555555557 38 101 99.9590277777778 104.666666666667 -4.70763888888888 1.04097222222222 39 95 94.8256944444445 103.958333333333 -9.13263888888888 0.174305555555563 40 93 91.7090277777778 103.416666666667 -11.7076388888889 1.29097222222224 41 84 85.0506944444444 103.125 -18.0743055555556 -1.05069444444446 42 87 87.0923611111111 103.166666666667 -16.0743055555556 -0.0923611111111171 43 116 117.259027777778 103.416666666667 13.8423611111111 -1.25902777777777 44 120 122.667361111111 103.916666666667 18.7506944444444 -2.66736111111111 45 117 122.892361111111 104.791666666667 18.1006944444444 -5.8923611111111 46 109 115.584027777778 105.916666666667 9.66736111111111 -6.58402777777778 47 105 109.009027777778 107.125 1.88402777777778 -4.00902777777779 48 107 107.909027777778 108.416666666667 -0.50763888888889 -0.909027777777766 49 109 107.667361111111 109.708333333333 -2.04097222222222 1.33263888888891 50 109 106.334027777778 111.041666666667 -4.70763888888888 2.66597222222222 51 108 103.367361111111 112.5 -9.13263888888888 4.63263888888891 52 107 102.167361111111 113.875 -11.7076388888889 4.83263888888889 53 99 96.9673611111111 115.041666666667 -18.0743055555556 2.0326388888889 54 103 100.092361111111 116.166666666667 -16.0743055555556 2.90763888888891 55 131 131.092361111111 117.25 13.8423611111111 -0.0923611111110887 56 137 136.875694444444 118.125 18.7506944444444 0.124305555555566 57 135 136.809027777778 118.708333333333 18.1006944444444 -1.80902777777777 58 124 128.584027777778 118.916666666667 9.66736111111111 -4.58402777777776 59 118 120.842361111111 118.958333333333 1.88402777777778 -2.8423611111111 60 121 118.450694444444 118.958333333333 -0.50763888888889 2.54930555555556 61 121 116.834027777778 118.875 -2.04097222222222 4.16597222222225 62 118 114.084027777778 118.791666666667 -4.70763888888888 3.91597222222225 63 113 109.534027777778 118.666666666667 -9.13263888888888 3.46597222222226 64 107 106.709027777778 118.416666666667 -11.7076388888889 0.290972222222251 65 100 99.9256944444444 118 -18.0743055555556 0.0743055555555685 66 102 101.175694444444 117.25 -16.0743055555556 0.824305555555569 67 130 130.134027777778 116.291666666667 13.8423611111111 -0.13402777777776 68 136 NA NA 18.7506944444444 NA 69 133 NA NA 18.1006944444444 NA 70 120 NA NA 9.66736111111111 NA 71 112 NA NA 1.88402777777778 NA 72 109 NA NA -0.50763888888889 NA 73 110 NA NA NA NA

Charts produced by software:

http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/1lwhc1305558824.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/1lwhc1305558824.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/2rj471305558824.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/2rj471305558824.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/342gc1305558824.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/342gc1305558824.ps (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/4ex3c1305558824.png (open in new window) http://www.freestatistics.org/blog/date/2011/May/16/t1305558659uthgk5m1vsgu5on/4ex3c1305558824.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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