*Unverified author*

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

Title produced by software: Structural Time Series Models

Date of computation: Fri, 04 Dec 2009 07:53:13 -0700

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf.htm/, Retrieved Fri, 04 Dec 2009 15:55:03 +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/2009/Dec/04/t1259938496lnitr6p6ur7nxsf.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:

WS9

Dataseries X:

» Textbox « » Textfile « » CSV «

106370 109375 116476 123297 114813 117925 126466 131235 120546 123791 129813 133463 122987 125418 130199 133016 121454 122044 128313 131556 120027 123001 130111 132524 123742 124931 133646 136557 127509 128945 137191 139716 129083 131604 139413 143125 133948 137116 144864 149277 138796 143258 150034 154708 144888 148762 156500 161088 152772 158011 163318 169969 162269 165765 170600 174681 166364 170240 176150 182056 172218 177856 182253 188090 176863 183273 187969 194650 183036 189516 193805 200499 188142 193732 197126 205140 191751 196700 199784 207360 196101 200824 205743 212489 200810 203683 207286 210910 194915 217920

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 3 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 106370 106370 0 0 0 2 109375 108922.636126821 728.117486074552 452.363873178612 0.53976180342067 3 116476 112678.716650195 1500.84894217363 3797.28334980506 1.84863387241178 4 123297 117660.813074953 2302.65564548320 5636.18692504668 3.22371511887175 5 114813 120021.844431290 2313.72369869994 -5208.84443128976 0.0542558685507608 6 117925 121405.774176828 2120.59311952945 -3480.77417682802 -0.836149363249779 7 126466 123780.972272063 2176.91281018991 2685.02772793657 0.220212956480617 8 131235 125777.031444316 2136.47200744301 5457.96855568442 -0.156203119766590 9 120546 126700.837954744 1866.19469106145 -6154.83795474398 -1.05231160837369 10 123791 127779.228249217 1690.53239716189 -3988.22824921662 -0.683042197653349 11 129813 128095.481442770 1383.3285582828 1717.51855723018 -1.18980920536799 12 133463 128154.951678300 1086.98611139037 5308.04832169982 -1.14527250110319 13 122987 128596.102786079 942.376065733486 -5609.10278607887 -0.558698997672846 14 125418 128877.507761650 794.369139382407 -3459.50776165024 -0.571797086477347 15 130199 128609.375783647 556.429347814278 1589.62421635329 -0.919108483204108 16 133016 128067.596183975 310.473168784701 4948.4038160248 -0.94995527225756 17 121454 127295.030087311 67.905321585922 -5841.03008731097 -0.936817030554 18 122044 125935.259207793 -251.854576985965 -3891.25920779303 -1.23491973534993 19 128313 125477.442227980 -297.984707970172 2835.55777201953 -0.178154160893119 20 131556 125372.959262827 -254.645247601705 6183.04073717347 0.167375519863296 21 120027 125119.388257161 -254.404644123481 -5092.3882571613 0.000929198649321629 22 123001 125741.574038062 -58.0699420297922 -2740.5740380617 0.758233468448591 23 130111 126628.305712260 153.542504340716 3482.69428774023 0.817234630321607 24 132524 126863.120825001 171.745585518399 5660.8791749995 0.070299182584383 25 123742 128166.643478809 425.236078248037 -4424.64347880856 0.978964468090956 26 124931 128657.546233033 439.943815450632 -3726.54623303296 0.0568003552385746 27 133646 129716.030049186 578.481728021924 3929.9699508136 0.535024660628051 28 136557 130981.492049868 732.3486001475 5575.50795013153 0.594224113316412 29 127509 132029.793728439 803.114405912926 -4520.79372843921 0.273293054024037 30 128945 133045.084457054 850.636742530929 -4100.0844570537 0.183528248297534 31 137191 133856.146766401 841.773031828317 3334.85323359930 -0.0342310880615040 32 139716 134538.370247873 806.037812242802 5177.62975212698 -0.138007149170096 33 129083 134579.516085602 634.720609314018 -5496.51608560233 -0.661616159639324 34 131604 135250.151089242 642.764560341107 -3646.15108924178 0.0310652280783169 35 139413 135871.754021700 638.024870264525 3541.24597829978 -0.0183043820992696 36 143125 136962.93580267 739.520999250287 6162.06419732995 0.391971604920762 37 133948 138585.198768345 937.233734896174 -4637.19876834519 0.763554029794596 38 137116 140299.452987577 1111.26742929422 -3183.45298757669 0.67210707613579 39 144864 141728.812737371 1182.51237432908 3135.18726262934 0.275143453461322 40 149277 143362.066795823 1283.46755130475 5914.93320417695 0.38988248252316 41 138796 144419.044267070 1232.739280721 -5623.04426707025 -0.195909359595220 42 143258 146080.734896432 1328.81395240476 -2822.73489643150 0.371034281007554 43 150034 147360.701589190 1317.87335401739 2673.29841081021 -0.0422518962105180 44 154708 148703.629540651 1323.48497461555 6004.3704593485 0.0216717223949620 45 144888 150351.849935064 1396.2178123606 -5463.84993506396 0.280889600612782 46 148762 151732.454626943 1392.72085302249 -2970.45462694307 -0.0135050348961255 47 156500 153473.462277217 1470.72862664035 3026.53772278332 0.301261067978768 48 161088 155158.680360436 1518.76904937325 5929.31963956397 0.185529061879942 49 152772 157450.074448638 1691.81827086577 -4678.07444863779 0.668305104246513 50 158011 160234.864466687 1936.61736545650 -2223.86446668660 0.94539855781426 51 163318 161681.337709857 1826.83700044343 1636.66229014347 -0.423964798289767 52 169969 163940.280021584 1923.61808306773 6028.71997841613 0.373762395198737 53 162269 166666.236813641 2103.32244415666 -4397.2368136413 0.694006830745987 54 165765 168504.428892983 2043.93968936677 -2739.42889298285 -0.229332428011046 55 170600 169965.371509808 1913.36252131543 634.628490192199 -0.504280730962624 56 174681 170485.205439525 1601.24600193717 4195.794560475 -1.20537417748022 57 166364 171081.278972308 1376.11181069139 -4717.27897230773 -0.86945394987783 58 170240 172206.201926985 1319.85161487017 -1966.20192698485 -0.217273303566137 59 176150 173924.213949574 1409.02986450265 2225.78605042581 0.34440073698758 60 182056 176275.370226149 1620.04327199434 5780.62977385119 0.814920379732723 61 172218 177635.247460099 1561.77240568825 -5417.24746009915 -0.225038385294920 62 177856 179611.357059447 1654.57386201560 -1755.35705944735 0.358393331158385 63 182253 181006.844477067 1596.54479843522 1246.15552293290 -0.224104558523441 64 188090 182391.690147019 1549.12934134595 5698.30985298091 -0.183115484251453 65 176863 183230.786449023 1390.09920574695 -6367.78644902319 -0.614164284780776 66 183273 184571.581464530 1379.05626601723 -1298.58146452955 -0.0426471319755319 67 187969 186167.263416092 1427.57515209384 1801.73658390819 0.187376856929387 68 194650 188066.865843553 1533.29778392748 6583.1341564472 0.408294090429373 69 183036 189618.241037839 1537.34668427623 -6582.24103783894 0.0156365960292397 70 189516 191104.778760675 1525.96671238795 -1588.77876067512 -0.0439487287693232 71 193805 192458.110702252 1487.30072152546 1346.88929774847 -0.149325601301638 72 200499 193896.004962966 1476.23487567473 6602.9950370343 -0.0427355939603103 73 188142 195042.333226721 1402.34381663732 -6900.33322672124 -0.285362577693019 74 193732 195824.152219180 1263.36134474689 -2092.15221918033 -0.536741480626576 75 197126 196328.166239753 1093.28600847501 797.833760247265 -0.656820148375207 76 205140 197623.470045321 1138.53308274486 7516.52995467906 0.174741327501807 77 191751 198528.137587446 1086.15288833711 -6777.13758744632 -0.202288984499335 78 196700 199026.400332053 954.479791319815 -2326.40033205313 -0.508513139034264 79 199784 199440.804816082 833.516054995908 343.195183918381 -0.467154268113753 80 207360 199855.138482433 739.629392808128 7504.86151756699 -0.362584327277488 81 196101 201334.646858300 905.344294063595 -5233.64685829972 0.63998042524287 82 200824 202628.090447718 992.269099173051 -1804.09044771760 0.33569807734033 83 205743 204464.395889486 1181.31271626707 1278.60411051385 0.730074444366178 84 212489 205745.387006401 1203.63825422513 6743.61299359902 0.086219809853726 85 200810 206739.727155024 1156.76056787782 -5929.72715502414 -0.181038647796096 86 203683 206991.917888325 954.158920516609 -3308.91788832492 -0.78243469628147 87 207286 206893.445084279 718.395010082095 392.5549157207 -0.910505250364885 88 210910 205709.952628957 292.418464261533 5200.04737104314 -1.64509436913863 89 194915 202968.420047704 -387.112796165675 -8053.4200477037 -2.62430657544552 90 217920 209875.618460144 1246.63554557506 8044.38153985612 6.30943234775982

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/1d7u01259938389.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/1d7u01259938389.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/2zo061259938389.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/2zo061259938389.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/3udl41259938389.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/3udl41259938389.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/4ylea1259938389.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/4ylea1259938389.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/5metg1259938389.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/04/t1259938496lnitr6p6ur7nxsf/5metg1259938389.ps (open in new window)

Parameters (Session):

par1 = 4 ;

Parameters (R input):

par1 = 4 ;

R code (references can be found in the software module):

par1 <- as.numeric(par1) nx <- length(x) x <- ts(x,frequency=par1) m <- StructTS(x,type='BSM') m$coef m$fitted m$resid mylevel <- as.numeric(m$fitted[,'level']) myslope <- as.numeric(m$fitted[,'slope']) myseas <- as.numeric(m$fitted[,'sea']) myresid <- as.numeric(m$resid) myfit <- mylevel+myseas mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level') acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(mylevel,main='Level') spectrum(myseas,main='Seasonal') spectrum(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(mylevel,main='Level') cpgram(myseas,main='Seasonal') cpgram(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test1.png') plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b') grid() dev.off() bitmap(file='test5.png') op <- par(mfrow = c(2,2)) hist(m$resid,main='Residual Histogram') plot(density(m$resid),main='Residual Kernel Density') qqnorm(m$resid,main='Residual Normal QQ Plot') qqline(m$resid) plot(m$resid^2, myfit^2,main='Sq.Resid vs. Sq.Fit',xlab='Squared residuals',ylab='Squared Fit') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Structural Time Series Model',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observed',header=TRUE) a<-table.element(a,'Level',header=TRUE) a<-table.element(a,'Slope',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Stand. Residuals',header=TRUE) a<-table.row.end(a) for (i in 1:nx) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) a<-table.element(a,mylevel[i]) a<-table.element(a,myslope[i]) a<-table.element(a,myseas[i]) a<-table.element(a,myresid[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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