Opgave 9 oefening 2 - Renske van der Eijk - Decompositiemodel

*Unverified author*

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

Title produced by software: Classical Decomposition

Date of computation: Wed, 03 Jun 2009 03:11:31 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn.htm/, Retrieved Wed, 03 Jun 2009 11:12:15 +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/2009/Jun/03/t12440203309twloq40ss2hcfn.htm/}, year = {2009}, } @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 = {2009}, 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 «

464 675 703 887 1139 1077 1318 1260 1120 963 996 960 530 883 894 1045 1199 1287 1565 1577 1076 918 1008 1063 544 635 804 980 1018 1064 1404 1286 1104 999 996 1015 615 722 832 977 1270 1437 1520 1708 1151 934 1159 1209 699 830 996 1124 1458 1270 1753 2258 1208 1241 1265 1828 809 997 1164 1205 1538 1513 1378 2083 1357 1536 1526 1376

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 4 seconds R Server 'George Udny Yule' @ 72.249.76.132 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 464 NA NA -497.527777777778 NA 2 675 NA NA -330.886111111111 NA 3 703 NA NA -215.119444444444 NA 4 887 NA NA -93.6694444444444 NA 5 1139 NA NA 127.538888888889 NA 6 1077 NA NA 137.255555555556 NA 7 1318 1376.96388888889 966.25 410.713888888889 -58.9638888888888 8 1260 1488.62222222222 977.666666666667 510.955555555556 -228.622222222222 9 1120 1012.72222222222 994.291666666667 18.4305555555556 107.277777777778 10 963 899.972222222222 1008.83333333333 -108.861111111111 63.0277777777777 11 996 976.880555555556 1017.91666666667 -41.036111111111 19.1194444444442 12 960 1111.37222222222 1029.16666666667 82.2055555555555 -151.372222222222 13 530 550.680555555555 1048.20833333333 -497.527777777778 -20.6805555555554 14 883 740.822222222222 1071.70833333333 -330.886111111111 142.177777777778 15 894 867.963888888889 1083.08333333333 -215.119444444444 26.0361111111113 16 1045 985.705555555556 1079.375 -93.6694444444444 59.2944444444445 17 1199 1205.53888888889 1078 127.538888888889 -6.53888888888878 18 1287 1220.04722222222 1082.79166666667 137.255555555556 66.9527777777778 19 1565 1498.38055555556 1087.66666666667 410.713888888889 66.6194444444445 20 1577 1588.87222222222 1077.91666666667 510.955555555556 -11.8722222222223 21 1076 1082.26388888889 1063.83333333333 18.4305555555556 -6.26388888888891 22 918 948.513888888889 1057.375 -108.861111111111 -30.5138888888887 23 1008 1006.08888888889 1047.125 -41.036111111111 1.91111111111127 24 1063 1112.49722222222 1030.29166666667 82.2055555555555 -49.497222222222 25 544 516.763888888889 1014.29166666667 -497.527777777778 27.2361111111112 26 635 664.572222222222 995.458333333333 -330.886111111111 -29.5722222222222 27 804 769.380555555556 984.5 -215.119444444444 34.6194444444444 28 980 895.372222222222 989.041666666667 -93.6694444444444 84.6277777777779 29 1018 1119.45555555556 991.916666666667 127.538888888889 -101.455555555556 30 1064 1126.67222222222 989.416666666667 137.255555555556 -62.672222222222 31 1404 1401.08888888889 990.375 410.713888888889 2.91111111111127 32 1286 1507.91388888889 996.958333333333 510.955555555556 -221.913888888889 33 1104 1020.18055555556 1001.75 18.4305555555556 83.8194444444445 34 999 893.930555555556 1002.79166666667 -108.861111111111 105.069444444444 35 996 972.130555555555 1013.16666666667 -41.036111111111 23.8694444444445 36 1015 1121.41388888889 1039.20833333333 82.2055555555555 -106.413888888889 37 615 562.055555555555 1059.58333333333 -497.527777777778 52.9444444444446 38 722 751.113888888889 1082 -330.886111111111 -29.1138888888886 39 832 886.422222222222 1101.54166666667 -215.119444444444 -54.422222222222 40 977 1007.12222222222 1100.79166666667 -93.6694444444444 -30.1222222222220 41 1270 1232.41388888889 1104.875 127.538888888889 37.5861111111112 42 1437 1257.00555555556 1119.75 137.255555555556 179.994444444445 43 1520 1542.04722222222 1131.33333333333 410.713888888889 -22.0472222222222 44 1708 1650.28888888889 1139.33333333333 510.955555555556 57.7111111111112 45 1151 1169.09722222222 1150.66666666667 18.4305555555556 -18.0972222222224 46 934 1054.76388888889 1163.625 -108.861111111111 -120.763888888889 47 1159 1136.54722222222 1177.58333333333 -41.036111111111 22.4527777777778 48 1209 1260.66388888889 1178.45833333333 82.2055555555555 -51.663888888889 49 699 683.680555555555 1181.20833333333 -497.527777777778 15.3194444444446 50 830 882.947222222222 1213.83333333333 -330.886111111111 -52.9472222222223 51 996 1024.00555555556 1239.125 -215.119444444444 -28.0055555555552 52 1124 1160.62222222222 1254.29166666667 -93.6694444444444 -36.6222222222220 53 1458 1399.03888888889 1271.5 127.538888888889 58.9611111111112 54 1270 1438.96388888889 1301.70833333333 137.255555555556 -168.963888888889 55 1753 1742.79722222222 1332.08333333333 410.713888888889 10.2027777777776 56 2258 1854.58055555556 1343.625 510.955555555556 403.419444444444 57 1208 1376.01388888889 1357.58333333333 18.4305555555556 -168.013888888889 58 1241 1259.09722222222 1367.95833333333 -108.861111111111 -18.0972222222219 59 1265 1333.63055555556 1374.66666666667 -41.036111111111 -68.6305555555552 60 1828 1470.33055555556 1388.125 82.2055555555555 357.669444444445 61 809 885.097222222222 1382.625 -497.527777777778 -76.0972222222222 62 997 1028.82222222222 1359.70833333333 -330.886111111111 -31.8222222222223 63 1164 1143.50555555556 1358.625 -215.119444444444 20.4944444444445 64 1205 1283.45555555556 1377.125 -93.6694444444444 -78.4555555555553 65 1538 1527.83055555556 1400.29166666667 127.538888888889 10.1694444444447 66 1513 1529.58888888889 1392.33333333333 137.255555555556 -16.5888888888890 67 1378 NA NA 410.713888888889 NA 68 2083 NA NA 510.955555555556 NA 69 1357 NA NA 18.4305555555556 NA 70 1536 NA NA -108.861111111111 NA 71 1526 NA NA -41.036111111111 NA 72 1376 NA NA 82.2055555555555 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/1hxrc1244020287.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/1hxrc1244020287.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/202da1244020287.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/202da1244020287.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/3afw21244020287.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/3afw21244020287.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/4caao1244020287.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t12440203309twloq40ss2hcfn/4caao1244020287.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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