STSM Dollar

*The author of this computation has been verified*

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

Title produced by software: Structural Time Series Models

Date of computation: Sun, 26 Dec 2010 13:32:25 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z.htm/, Retrieved Sun, 26 Dec 2010 14:31:11 +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/2010/Dec/26/t1293370265yojxu3s9qh9tb3z.htm/}, year = {2010}, } @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 = {2010}, 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 «

0,8973 0,9383 0,9217 0,9095 0,892 0,8742 0,8532 0,8607 0,9005 0,9111 0,9059 0,8883 0,8924 0,8833 0,87 0,8758 0,8858 0,917 0,9554 0,9922 0,9778 0,9808 0,9811 1,0014 1,0183 1,0622 1,0773 1,0807 1,0848 1,1582 1,1663 1,1372 1,1139 1,1222 1,1692 1,1702 1,2286 1,2613 1,2646 1,2262 1,1985 1,2007 1,2138 1,2266 1,2176 1,2218 1,249 1,2991 1,3408 1,3119 1,3014 1,3201 1,2938 1,2694 1,2165 1,2037 1,2292 1,2256 1,2015 1,1786 1,1856 1,2103 1,1938 1,202 1,2271 1,277 1,265 1,2684 1,2811 1,2727 1,2611 1,2881 1,3213 1,2999 1,3074 1,3242 1,3516 1,3511 1,3419 1,3716 1,3622 1,3896 1,4227 1,4684 1,457 1,4718 1,4748 1,5527 1,575 1,5557 1,5553 1,577 1,4975 1,4369 1,3322 1,2732 1,3449 1,3239 1,2785 1,305 1,319 1,365 1,4016 1,4088 1,4268 1,4562 1,4816 1,4914 1,4614 1,4272 1,3686 1,3569 1,3406 1,2565 1,2208 1,277 1,2894 1,3067 1,3898 1,3661

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 22 seconds R Server 'George Udny Yule' @ 72.249.76.132 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 0.8973 0.8973 0 0 0 2 0.9383 0.936168000075857 0.00213199998160767 0.00213199992414349 0.719789379959892 3 0.9217 0.919642629485343 0.00205737051465687 0.00205737051465687 -0.576589013356853 4 0.9095 0.907499206351308 0.00200079364869197 0.00200079364869197 -0.43885908541227 5 0.892 0.890076284585504 0.00192371541449609 0.00192371541449609 -0.600262709021044 6 0.8742 0.87235393700682 0.00184606299317954 0.00184606299317955 -0.60712930680806 7 0.8532 0.851443529408905 0.00175647059109495 0.00175647059109495 -0.70324589433565 8 0.8607 0.858921093747603 0.00177890625239694 0.00177890625239694 0.176798275288377 9 0.9005 0.898573151751551 0.00192684824844891 0.00192684824844891 1.17038054590496 10 0.9111 0.909139534884968 0.00196046511503164 0.00196046511503164 0.266982454359909 11 0.9059 0.903967181467874 0.00193281853212590 0.00193281853212590 -0.22041963125948 12 0.8883 0.886442307691509 0.00185769230849109 0.00185769230849110 -0.601280598491724 13 0.8924 0.90504278200202 0.00114934384135221 -0.0126427820020193 0.625104324837924 14 0.8833 0.882718909243836 0.000581090917622456 0.00058109075616367 -0.617150691080449 15 0.87 0.869444101612688 0.000555898387311558 0.000555898387311558 -0.427738378143892 16 0.8758 0.875234601429086 0.00056539857091401 0.000565398570914008 0.161594444562762 17 0.8858 0.885217540667866 0.000582459332134159 0.000582459332134158 0.290723138479871 18 0.917 0.916362274351744 0.000637725648255614 0.000637725648255613 0.943467737986584 19 0.9554 0.954694234221186 0.000705765778814193 0.000705765778814188 1.16363185376618 20 0.9922 0.991429316536984 0.000770683463016112 0.000770683463016116 1.11223356048264 21 0.9778 0.977056552951177 0.000743447048822653 0.000743447048822651 -0.467481051705424 22 0.9808 0.980052508949674 0.000747491050325773 0.000747491050325774 0.0695352618423683 23 0.9811 0.980353309470297 0.00074669052970311 0.00074669052970311 -0.0137893760960925 24 1.0014 1.00061839284798 0.000781607152023652 0.000781607152023657 0.602533546637026 25 1.0183 1.02236725398745 0.000369750381056052 -0.00406725398745186 0.713132395721076 26 1.0622 1.06123235325218 0.00096764709214039 0.000967646747823025 1.07923218202040 27 1.0773 1.07631574616116 0.000984253838836316 0.000984253838836316 0.435620405996686 28 1.0807 1.07971291077858 0.000987089221424175 0.000987089221424176 0.0744638262205396 29 1.0848 1.08380926141102 0.00099073858898093 0.000990738588980925 0.0959535445590255 30 1.1582 1.15712447305558 0.001075526944415 0.00107552694441500 2.23197211870050 31 1.1663 1.16521625729829 0.00108374270170946 0.00108374270170946 0.216525323582058 32 1.1372 1.1361515186771 0.0010484813229006 0.00104848132290060 -0.930397066629317 33 1.1139 1.11287992997156 0.00102007002843637 0.00102007002843637 -0.750528895038914 34 1.1222 1.12117144520538 0.00102855479461833 0.00102855479461833 0.224400094803468 35 1.1692 1.16811792781132 0.00108207218868132 0.00108207218868132 1.41704710199551 36 1.1702 1.16911802324409 0.00108197675591146 0.00108197675591147 -0.00252983641068476 37 1.2286 1.23183047910256 0.000293679943058873 -0.00323047910255836 2.03015823521528 38 1.2613 1.26067982641986 0.000620173951783961 0.000620173580140559 0.822743273075176 39 1.2646 1.26397749779210 0.000622502207895658 0.000622502207895656 0.0826165150682867 40 1.2262 1.22561137148813 0.000588628511868732 0.000588628511868731 -1.20302763429544 41 1.1985 1.19793590628894 0.00056409371105703 0.000564093711057025 -0.872112569222154 42 1.2007 1.20013448869266 0.000565511307335573 0.000565511307335569 0.0504335151012443 43 1.2138 1.21322363632272 0.000576363677281762 0.000576363677281757 0.386427123844363 44 1.2266 1.22601306224404 0.000586937755961629 0.000586937755961631 0.376843963350759 45 1.2176 1.21702134827402 0.00057865172598466 0.000578651725984655 -0.295556974759445 46 1.2218 1.22121822103061 0.000581778969395024 0.000581778969395023 0.111643067623664 47 1.249 1.24839525449216 0.000604745507839922 0.000604745507839924 0.820617276699492 48 1.2991 1.29845258617408 0.000647413825916506 0.000647413825916513 1.52589746785340 49 1.3408 1.34330999224743 0.000228181150751563 -0.00250999224743125 1.43289733918776 50 1.3119 1.31195751751124 -5.75172094124582e-05 -5.75175112391054e-05 -0.923787347527385 51 1.3014 1.30146471394875 -6.47139487463972e-05 -6.47139487463975e-05 -0.321960909050973 52 1.3201 1.32015179059389 -5.17905938875944e-05 -5.17905938875955e-05 0.578550687159317 53 1.2938 1.29386985542915 -6.98554291530096e-05 -6.98554291530128e-05 -0.809280825252152 54 1.2694 1.26948658867612 -8.65886761151433e-05 -8.6588676115135e-05 -0.75014351780507 55 1.2165 1.21662288654811 -0.000122886548113697 -0.000122886548113710 -1.62833588646427 56 1.2037 1.20383159335556 -0.000131593355556708 -0.000131593355556709 -0.390859123249421 57 1.2292 1.2293140013242 -0.000114001324198682 -0.000114001324198687 0.790270159476723 58 1.2256 1.22571639226945 -0.000116392269450691 -0.000116392269450689 -0.107479911221673 59 1.2015 1.20163283065485 -0.000132830654854464 -0.000132830654854457 -0.739460015823206 60 1.1786 1.17874842460423 -0.000148424604234408 -0.000148424604234397 -0.701955083145818 61 1.1856 1.18355654658199 -0.000185768447181241 0.00204345341800604 0.159080800000323 62 1.2103 1.21028434338108 1.56572096051783e-05 1.56566189187376e-05 0.794887083394606 63 1.1938 1.19379377490366 6.22509633846648e-06 6.22509633846237e-06 -0.509238108595697 64 1.202 1.20198909809232 1.09019076806727e-05 1.09019076806693e-05 0.252644075485236 65 1.2271 1.22707478600235 2.52139976462872e-05 2.52139976462837e-05 0.77358886463599 66 1.277 1.27694635112362 5.36488763778315e-05 5.36488763778158e-05 1.53782273133959 67 1.265 1.26495321929842 4.67807015782706e-05 4.67807015782585e-05 -0.371658301438412 68 1.2684 1.26835130972057 4.86902794334402e-05 4.86902794334381e-05 0.103392093456135 69 1.2811 1.28104410920405 5.58907959477543e-05 5.58907959477515e-05 0.390086508713718 70 1.2727 1.27264891915247 5.10808475273547e-05 5.10808475273545e-05 -0.260726322077641 71 1.2611 1.26105554284708 4.44571529172106e-05 4.44571529172181e-05 -0.359245882233398 72 1.2881 1.28804022720040 5.97727995974264e-05 5.97727995974367e-05 0.831139141747973 73 1.3213 1.31977953232277 -0.000138224269761954 0.00152046767723252 1.01010353885725 74 1.2999 1.30016253715576 -0.000262536511629337 -0.000262537155756682 -0.579149806124275 75 1.3074 1.30765875176239 -0.00025875176239054 -0.000258751762390547 0.239357361856446 76 1.3242 1.32445043853225 -0.000250438532250292 -0.000250438532250294 0.526005722246638 77 1.3516 1.35183697022595 -0.000236970225948186 -0.000236970225948189 0.852599933467548 78 1.3511 1.35133709828326 -0.000237098283260704 -0.000237098283260719 -0.00811051131064872 79 1.3419 1.34214145979171 -0.000241459791714629 -0.000241459791714642 -0.276370706043170 80 1.3716 1.37182689682788 -0.000226896827884425 -0.000226896827884425 0.923243791336669 81 1.3622 1.36243135628403 -0.000231356284027731 -0.000231356284027736 -0.282852326226023 82 1.3896 1.38981792997178 -0.000217929971779064 -0.000217929971779063 0.85201203765279 83 1.4227 1.42290174836754 -0.000201748367538827 -0.000201748367538817 1.02735748709004 84 1.4684 1.46857946596999 -0.000179465969991662 -0.000179465969991654 1.41537936052940 85 1.457 1.45576785886849 -0.000112012792309105 0.00123214113150733 -0.400885417667154 86 1.4718 1.47182208552311 -2.20850528384655e-05 -2.20855231064326e-05 0.483015563945238 87 1.4748 1.47482079960929 -2.07996092865899e-05 -2.07996092865991e-05 0.0931887102666743 88 1.5527 1.55268767002548 1.23299745226668e-05 1.23299745226656e-05 2.40275850807065 89 1.575 1.57497819800476 2.18019952362484e-05 2.1801995236246e-05 0.687260575964102 90 1.5557 1.55568640607503 1.35939249668178e-05 1.35939249668084e-05 -0.595805391588276 91 1.5553 1.55528658169874 1.34183012611066e-05 1.34183012610881e-05 -0.0127535471442651 92 1.577 1.57697737686998 2.26231300223300e-05 2.26231300223298e-05 0.668725651736666 93 1.4975 1.49751111577719 -1.11157771902430e-05 -1.11157771902597e-05 -2.45215329503835 94 1.4369 1.43693681080259 -3.68108025855725e-05 -3.68108025855654e-05 -1.86831419303888 95 1.3322 1.33228117840090 -8.11784009049724e-05 -8.11784009049554e-05 -3.22738637555187 96 1.2732 1.27330614399737 -0.000106143997373435 -0.000106143997373419 -1.81681659651114 97 1.3449 1.34029250321298 -0.000418863275201434 0.00460749678701518 2.12168274049330 98 1.3239 1.32439517043736 -0.000495169729131669 -0.000495170437359888 -0.464198006944616 99 1.2785 1.27901210851334 -0.00051210851334077 -0.000512108513340797 -1.38471439959318 100 1.305 1.30550192295480 -0.000501922954796684 -0.000501922954796686 0.832962897304774 101 1.319 1.3194964567207 -0.000496456720698833 -0.000496456720698833 0.447190733508145 102 1.365 1.36547893733704 -0.000478937337035333 -0.000478937337035358 1.43379509933716 103 1.4016 1.40206497163934 -0.000464971639336542 -0.000464971639336559 1.14339040360970 104 1.4088 1.40926208573211 -0.000462085732113682 -0.000462085732113683 0.236362103863591 105 1.4268 1.42725513726362 -0.000455137263621688 -0.000455137263621696 0.569309051615043 106 1.4562 1.45664390508557 -0.000443905085569105 -0.000443905085569103 0.920632767706364 107 1.4816 1.48203418568047 -0.000434185680468259 -0.000434185680468246 0.796939814445722 108 1.4914 1.49183033824327 -0.000430338243272688 -0.000430338243272666 0.315588166222294 109 1.4614 1.45817752628093 -0.000292952082180122 0.00322247371907478 -1.04770908504202 110 1.4272 1.42762688198742 -0.000426881272697738 -0.000426881987422614 -0.910106933769154 111 1.3686 1.36904659423600 -0.000446594236002106 -0.000446594236002148 -1.79389832891346 112 1.3569 1.35735040636418 -0.000450406364182928 -0.000450406364182928 -0.347023970123027 113 1.3406 1.34105577364792 -0.000455773647923225 -0.000455773647923226 -0.488757744923583 114 1.2565 1.25698408922047 -0.000484089220465286 -0.000484089220465286 -2.57935734701830 115 1.2208 1.22129600661479 -0.000496006614790545 -0.000496006614790565 -1.08596166606329 116 1.277 1.27747682664536 -0.00047682664535952 -0.000476826645359518 1.74834874251846 117 1.2894 1.28987247195385 -0.000472471953850926 -0.000472471953850936 0.397085902614751 118 1.3067 1.30716646368251 -0.00046646368250685 -0.000466463682506847 0.548054164694782 119 1.3898 1.39023822223652 -0.000438222236516553 -0.000438222236516546 2.57696009795879 120 1.3661 1.36654608094287 -0.000446080942870452 -0.000446080942870432 -0.717329343443493

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/1dwvg1293370322.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/1dwvg1293370322.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/265c11293370322.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/265c11293370322.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/365c11293370322.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/365c11293370322.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/4gxt41293370322.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/4gxt41293370322.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/5r6a71293370322.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293370265yojxu3s9qh9tb3z/5r6a71293370322.ps (open in new window)

Parameters (Session):

par1 = 12 ;

Parameters (R input):

par1 = 12 ;

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$resid) myfit <- mylevel+myseas bitmap(file='test1.png') plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time') grid() dev.off() 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='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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