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 09:25:16 -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/t1244042769ommu27y1voch26f.htm/, Retrieved Wed, 03 Jun 2009 17:26:14 +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/t1244042769ommu27y1voch26f.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 1 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Classical Decomposition by Moving Averages t Observations Fit Trend Seasonal Random 1 464 NA NA 0.559511314301936 NA 2 675 NA NA 0.708793417842948 NA 3 703 NA NA 0.811090709588377 NA 4 887 NA NA 0.922975029059648 NA 5 1139 NA NA 1.10592810920734 NA 6 1077 NA NA 1.12123713443669 NA 7 1318 1328.76382904756 966.25 1.37517601971287 0.991899366304034 8 1260 1411.15709977247 977.666666666667 1.44339287395752 0.892884286379706 9 1120 1019.53045282642 994.291666666667 1.02538368469321 1.09854492025722 10 963 913.210181770244 1008.83333333333 0.905214123677757 1.05452175109704 11 996 982.4242304941 1017.91666666667 0.965132277194367 1.01381864278640 12 960 1086.97012776188 1029.16666666667 1.05616530632733 0.88318894464624 13 530 586.484422245575 1048.20833333333 0.559511314301936 0.903689816637749 14 883 759.619812514103 1071.70833333333 0.708793417842948 1.16242360382564 15 894 878.478829376678 1083.08333333333 0.811090709588377 1.01766823525427 16 1045 996.236171991257 1079.375 0.922975029059648 1.04894806008828 17 1199 1192.19050172552 1078 1.10592810920734 1.00571175350301 18 1287 1214.06622552526 1082.79166666667 1.12123713443669 1.06007396708790 19 1565 1495.73311744103 1087.66666666667 1.37517601971287 1.04630965360817 20 1577 1555.85723538672 1077.91666666667 1.44339287395752 1.01358914181354 21 1076 1090.83734323279 1063.83333333333 1.02538368469321 0.98639820746435 22 918 957.150784023768 1057.375 0.905214123677757 0.959096534551033 23 1008 1010.61413575715 1047.125 0.965132277194367 0.997413319619567 24 1063 1088.15831373149 1030.29166666667 1.05616530632733 0.97687991405844 25 544 567.507663502168 1014.29166666667 0.559511314301936 0.958577363771444 26 635 705.574314403578 995.458333333333 0.708793417842948 0.899976072026893 27 804 798.518803589757 984.5 0.811090709588377 1.00686420455674 28 980 912.860761032869 989.041666666667 0.922975029059648 1.07354817057879 29 1018 1096.98852365792 991.916666666667 1.10592810920734 0.927995123053313 30 1064 1109.37070809723 989.416666666667 1.12123713443669 0.959102302083446 31 1404 1361.93995052314 990.375 1.37517601971287 1.03088245517778 32 1286 1439.00255396590 996.958333333333 1.44339287395752 0.893674577891313 33 1104 1027.17810614142 1001.75 1.02538368469321 1.07478926332178 34 999 907.741179773024 1002.79166666667 0.905214123677757 1.10053396525406 35 996 977.839852177426 1013.16666666667 0.965132277194367 1.01857169942720 36 1015 1097.57578771291 1039.20833333333 1.05616530632733 0.924765297633814 37 615 592.84886344576 1059.58333333333 0.559511314301936 1.03736388465939 38 722 766.91447810607 1082 0.708793417842948 0.941434828278392 39 832 893.45021205783 1101.54166666667 0.811090709588377 0.931221447789133 40 977 1016.00322053028 1100.79166666667 0.922975029059648 0.96161112510064 41 1270 1221.91231966046 1104.875 1.10592810920734 1.03935444431307 42 1437 1255.50528128548 1119.75 1.12123713443669 1.14455910414705 43 1520 1555.78247030183 1131.33333333333 1.37517601971287 0.977000338424634 44 1708 1644.50561439561 1139.33333333333 1.44339287395752 1.03861001449225 45 1151 1179.87482652032 1150.66666666667 1.02538368469321 0.975527211979362 46 934 1053.32978466453 1163.625 0.905214123677757 0.886711848082285 47 1159 1136.52368408613 1177.58333333333 0.965132277194367 1.01977637266041 48 1209 1244.64680661899 1178.45833333333 1.05616530632733 0.971359901918018 49 699 660.899427047733 1181.20833333333 0.559511314301936 1.05764957782225 50 830 860.357077025032 1213.83333333333 0.708793417842948 0.964715723464493 51 996 1005.04277551870 1239.125 0.811090709588377 0.99100259636807 52 1124 1157.67988749094 1254.29166666667 0.922975029059648 0.970907426262768 53 1458 1406.18759085714 1271.5 1.10592810920734 1.03684601505499 54 1270 1459.52372153903 1301.70833333333 1.12123713443669 0.870146871378577 55 1753 1831.84905625919 1332.08333333333 1.37517601971287 0.956956575657928 56 2258 1939.37875027118 1343.625 1.44339287395752 1.16429036859575 57 1208 1392.04380061142 1357.58333333333 1.02538368469321 0.867788786149843 58 1241 1238.29520393602 1367.95833333333 0.905214123677757 1.00218429018814 59 1265 1326.73517038319 1374.66666666667 0.965132277194367 0.953468354678983 60 1828 1466.08946584562 1388.125 1.05616530632733 1.24685433091604 61 809 773.594330936714 1382.625 0.559511314301936 1.04576774628172 62 997 963.752316852872 1359.70833333333 0.708793417842948 1.03449816157713 63 1164 1101.96811531451 1358.625 0.811090709588377 1.05629190520434 64 1205 1271.05198689377 1377.125 0.922975029059648 0.948033607142076 65 1538 1548.62191525546 1400.29166666667 1.10592810920734 0.993141053248163 66 1513 1561.13583684735 1392.33333333333 1.12123713443669 0.969166144475577 67 1378 NA NA 1.37517601971287 NA 68 2083 NA NA 1.44339287395752 NA 69 1357 NA NA 1.02538368469321 NA 70 1536 NA NA 0.905214123677757 NA 71 1526 NA NA 0.965132277194367 NA 72 1376 NA NA 1.05616530632733 NA

Charts produced by software:

http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/1x9lz1244042714.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/1x9lz1244042714.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/24f831244042714.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/24f831244042714.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/3ad811244042714.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/3ad811244042714.ps (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/4kfx81244042714.png (open in new window) http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2009/Jun/03/t1244042769ommu27y1voch26f/4kfx81244042714.ps (open in new window)

Parameters (Session):

par1 = multiplicative ; par2 = 12 ;

Parameters (R input):

par1 = multiplicative ; 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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