workshop8

*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, 19 Dec 2010 00:34:57 +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/19/t1292718784q1c9qm98q0heihq.htm/, Retrieved Sun, 19 Dec 2010 01:33:04 +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/19/t1292718784q1c9qm98q0heihq.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 «

40.7819 39.5915 38.8859 39.9068 41.47 41.5613 41.6005 41.4113 41.84 42.2892 43.1521 43.5998 43.116 42.4185 42.3687 42.2975 42.8528 43.535 44.7265 45.7293 45.7585 46.1685 46.5075 46.527 46.601 46.4607 46.7135 46.4113 45.55 44.6081 44.4395 44.9847 45.7558 45.3942 45.697 45.5664 46.0205 45.9195 45.8005 45.535 45.4977 45.5782 45.7697 45.2445 45.0615 45.2865 44.791 44.7625 44.7644 44.9973 44.7265 45.1465 44.7465 45.1795 45.6515 45.492 45.2775 45.2115 45.411 45.4005 44.7692 44.8913 45.032 44.879 44.833 44.8257 44.7815 44.479 44.6317 44.5043 44.3217 44.1005 44.047 43.6835 43.7864 44.1807 43.9595 43.937 43.991 43.865 43.671 43.93 43.863 43.7095 43.9435 43.736 43.6295 43.598 43.8726 43.8935 43.5957 43.7155 43.528 43.3415 43.3374 43.332 43.3869 43.5016 43.4875 43.6023 43.3886 43.3105 43.4455 43.5185 43.5755 43.6217 43.644 43.5789 43.5215 43.5033 43.632 43.263 43.3717 43.2745 43.2647 43.324 43.4455 43.409 etc...

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 13 seconds R Server 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 40.7819 40.7819 0 0 0 2 39.5915 39.770059994133 -0.178559994133014 -0.178559994133014 -1.36970783676373 3 38.8859 39.0773146280104 -0.191414628010389 -0.191414628010389 -1.89415976807075 4 39.9068 40.0693499949134 -0.162549994913386 -0.162549994913386 4.35830467363426 5 41.47 41.5924162753281 -0.122416275328121 -0.122416275328121 6.20587832691626 6 41.5613 41.1796661101963 -0.0954084724509335 0.381633889803734 -1.23744090232837 7 41.6005 41.6572778939513 -0.056777893951332 -0.0567778939513321 1.75389155075320 8 41.4113 41.4694572908705 -0.0581572908704544 -0.0581572908704543 -0.479315678378071 9 41.84 41.8931381436099 -0.0531381436098989 -0.0531381436098989 1.76232655664754 10 42.2892 42.3372122442541 -0.0480122442540517 -0.0480122442540519 1.81846080109178 11 43.1521 42.8658964945277 -0.071550876368076 0.286203505472304 2.2631933435711 12 43.5998 43.6362706663471 -0.0364706663471061 -0.0364706663471064 2.78191561455028 13 43.116 43.1554331122395 -0.0394331122395525 -0.039433112239552 -1.62225638459179 14 42.4185 42.4622624996216 -0.0437624996215947 -0.0437624996215944 -2.38655625920503 15 42.3687 42.412501960408 -0.0438019604080427 -0.0438019604080429 -0.0218961725953678 16 42.2975 42.1456207112403 -0.0379698221899149 0.151879288759660 -0.85308409707529 17 42.8528 42.8678492681962 -0.0150492681961934 -0.015049268196194 2.58719464757406 18 43.535 43.5466645630324 -0.0116645630323695 -0.0116645630323695 2.53084964888781 19 44.7265 44.7323521738759 -0.00585217387588033 -0.00585217387588052 4.36725376322014 20 45.7293 45.730302884609 -0.00100288460904112 -0.00100288460904152 3.66125427916204 21 45.7585 45.7526892857484 -0.00145267856289902 0.00581071425159628 0.0883169900733072 22 46.1685 46.1602900000415 0.00820999995850446 0.00820999995850391 1.41413842811856 23 46.5075 46.4980226054117 0.00947739458829671 0.00947739458829696 1.20130628882719 24 46.527 46.5174843511928 0.00951564880723346 0.00951564880723372 0.0363986435041660 25 46.601 46.5912391635469 0.00976083645312897 0.00976083645312856 0.234186612255391 26 46.4607 46.5055501790002 0.0112125447500536 -0.0448501790002141 -0.357712654239582 27 46.7135 46.6987536508552 0.0147463491448272 0.0147463491448267 0.635306933007834 28 46.4113 46.3975566456268 0.0137433543732240 0.0137433543732245 -1.15141649638900 29 45.55 45.5390170347458 0.0109829652541536 0.0109829652541545 -3.17891151293826 30 44.6081 44.6001135220456 0.00798647795441802 0.00798647795441792 -3.46170928063619 31 44.4395 44.4779922154174 0.0096230538543533 -0.0384922154174129 -0.48517444025897 32 44.9847 44.9671721622244 0.0175278377755807 0.01752783777558 1.68518586521926 33 45.7558 45.7362409704197 0.0195590295803107 0.0195590295803104 2.73825388277661 34 45.3942 45.3756655914633 0.0185344085366718 0.0185344085366725 -1.38502194808428 35 45.697 45.6777034853227 0.0192965146773199 0.0192965146773194 1.03294288015428 36 45.5664 45.6457830331508 0.0198457582877081 -0.0793830331508321 -0.190313325527375 37 46.0205 45.9959244706642 0.0245755293357698 0.0245755293357697 1.16625385800569 38 45.9195 45.8952192489012 0.0242807510988019 0.0242807510988013 -0.456383191585799 39 45.8005 45.7765548010105 0.0239451989895331 0.0239451989895340 -0.520731284112664 40 45.535 45.5117310748378 0.0232689251621949 0.0232689251621946 -1.05194579399783 41 45.4977 45.5887657654962 0.0227664413740536 -0.0910657654962142 0.199255534058522 42 45.5782 45.5561347917271 0.0220652082729197 0.0220652082729195 -0.19631714120677 43 45.7697 45.7472825364438 0.0224174635562131 0.0224174635562123 0.615865153510137 44 45.2445 45.2232186722572 0.0212813277428044 0.0212813277428056 -1.99049580478863 45 45.0615 45.0406416149636 0.0208583850364132 0.0208583850364129 -0.742529280106252 46 45.2865 45.3600438875819 0.0183859718954650 -0.0735438875818597 1.10412908288987 47 44.791 44.7794082243275 0.0115917756724607 0.0115917756724612 -2.12886909965005 48 44.7625 44.7509830224163 0.011516977583703 0.0115169775837017 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0.0149130863955575 0.0149130863955572 -1.15642697244522 73 44.047 44.032171270061 0.0148287299389796 0.0148287299389796 -0.248774707435861 74 43.6835 43.6691371921415 0.0143628078585281 0.0143628078585296 -1.37574104039236 75 43.7864 43.7719282903063 0.0144717096937045 0.0144717096937029 0.321953717915215 76 44.1807 44.2298594691621 0.0122898672905298 -0.049159469162119 1.62937438064446 77 43.9595 43.9492559537728 0.0102440462272116 0.0102440462272117 -1.05059825024064 78 43.937 43.9267937644497 0.0102062355503322 0.0102062355503315 -0.119073854059620 79 43.991 43.9807432526107 0.0102567473892979 0.0102567473892993 0.15925630440677 80 43.865 43.85490023043 0.0100997695699627 0.0100997695699619 -0.495498862598384 81 43.671 43.7141791854562 0.0107947963640432 -0.0431791854561725 -0.553812189033787 82 43.93 43.9179384782781 0.0120615217219014 0.0120615217219012 0.69276544833966 83 43.863 43.8510243214069 0.0119756785931185 0.0119756785931182 -0.287517461793379 84 43.7095 43.6977037961123 0.0117962038877419 0.0117962038877433 -0.601774088153797 85 43.9435 43.9314630552717 0.0120369447282575 0.0120369447282561 0.808073830400238 86 43.736 43.7868630457222 0.0127157614305533 -0.0508630457222124 -0.574858733445017 87 43.6295 43.6179091282208 0.0115908717792492 0.0115908717792491 -0.652722725795506 88 43.598 43.5864532787041 0.0115467212959283 0.0115467212959275 -0.156710334509682 89 43.8726 43.8607840327692 0.0118159672307801 0.0118159672307815 0.956657111708349 90 43.8935 43.8816747443922 0.0118252556078323 0.0118252556078308 0.0330363078788860 91 43.5957 43.6470331991273 0.0128332997818261 -0.0513331991273034 -0.904101419180115 92 43.7155 43.7024173786575 0.0130826213425315 0.0130826213425311 0.152987289320089 93 43.528 43.5151119301813 0.0128880698186840 0.0128880698186841 -0.729486972583141 94 43.3415 43.3288051356751 0.0126948643249197 0.0126948643249215 -0.725142920486282 95 43.3374 43.3247213940142 0.0126786059858069 0.0126786059858049 -0.0610802978050863 96 43.332 43.3820232601852 0.0125058150462970 -0.050023260185187 0.163619039265389 97 43.3869 43.3745055299689 0.0123944700310709 0.0123944700310702 -0.0720372458689374 98 43.5016 43.489111325982 0.0124886740180369 0.0124886740180365 0.372078027429651 99 43.4875 43.4750357865836 0.0124642134163940 0.0124642134163958 -0.0967011810381393 100 43.6023 43.5897417279563 0.012558272043655 0.0125582720436529 0.372188383897489 101 43.3886 43.4412021738504 0.0131505434626071 -0.0526021738504272 -0.590465771575757 102 43.3105 43.2981757894879 0.0123242105121091 0.0123242105121088 -0.562180453476978 103 43.4455 43.4330682734587 0.0124317265413348 0.0124317265413338 0.446173141411028 104 43.5185 43.5060152364417 0.0124847635583129 0.0124847635583150 0.220287534569897 105 43.5755 43.5629762904781 0.0125237095219091 0.0125237095219067 0.161902509121117 106 43.6217 43.6704654874339 0.0121913718584805 -0.048765487433921 0.34795202044807 107 43.644 43.6320639330675 0.0119360669324807 0.0119360669324808 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39.4398 39.4356289741427 0.00417102585725353 0.00417102585725206 0.195155357313528 431 39.2537 39.2709566962352 0.00431417405879481 -0.0172566962351761 -0.615394992584942 432 39.2301 39.22584807128 0.00425192872000343 0.00425192872000424 -0.179375803426355 433 39.2763 39.2720392789783 0.00426072102167357 0.00426072102167737 0.152616481438731 434 39.282 39.2777389773692 0.00426102263084749 0.00426102263084230 0.00523641949688783 435 39.3325 39.3282292897561 0.00427071024395382 0.00427071024395076 0.168227766522542 436 39.557 39.5732757151762 0.00406892879403967 -0.0162757151761572 0.877554991912926 437 40.1 40.0952861968925 0.00471380310752526 0.00471380310752359 1.87987885876153 438 40.5875 40.5826861583105 0.00481384168953084 0.00481384168953113 1.75648644690832 439 40.485 40.4802083903058 0.00479160969415892 0.00479160969415563 -0.390432273650850 440 40.55 40.5451959196368 0.00480408036323299 0.00480408036323113 0.219051884214778 441 40.7955 40.8138419487977 0.00458548719941686 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41.5690509717506 0.00544902824941688 0.00544902824941461 0.760730205993312 454 41.593 41.5875483573732 0.00545164262677007 0.00545164262676527 0.0474825795357609 455 41.575 41.5695530542774 0.00544694572258008 0.00544694572258122 -0.0853227276782544 456 41.68 41.7013827909706 0.0053456977426582 -0.0213827909706321 0.460593317619781 457 42.0055 41.9998053320134 0.00569466798662376 0.00569466798662648 1.06384463090228 458 42.3188 42.3130443717811 0.00575562821887342 0.00575562821886901 1.11914350753466 459 42.565 42.5591967307326 0.0058032692673613 0.00580326926735419 0.87479550866351 460 42.3575 42.3517389857384 0.00576101426157436 0.00576101426157968 -0.776049546175052 461 42.29 42.3131845181614 0.00579612954035968 -0.0231845181614384 -0.161501890063077 462 42.695 42.6887683137271 0.00623168627290387 0.00623168627290666 1.34233333554956 463 43.0028 42.9965091942773 0.00629080572274664 0.00629080572274312 1.09718052944034 464 42.4507 42.4445186397507 0.00618136024928948 0.00618136024928677 -2.0315646695714 465 42.4705 42.4643159709990 0.00618402900095463 0.00618402900095754 0.0495480004560491 466 42.2875 42.3127307872567 0.00630769681416479 -0.0252307872566569 -0.574959159809202 467 42.3172 42.3109017846767 0.00629821532332143 0.00629821532332895 -0.0295370581119908 468 42.55 42.5436578549279 0.00634214507208362 0.00634214507207198 0.824070688511897 469 42.7523 42.7459198565073 0.00638014349265329 0.00638014349264985 0.712944172592037 470 42.8993 42.8928925940303 0.00640740596967383 0.0064074059696751 0.511610566309624 471 43.1555 43.1802580981769 0.00618952454423324 -0.0247580981769334 1.02387999091796 472 43.1885 43.1823152399248 0.00618476007521477 0.00618476007522456 -0.0150013481060496 473 43.43 43.4237700825193 0.00622991748067711 0.00622991748066463 0.856137140710675 474 43.31 43.3037943016132 0.00620569838676906 0.00620569838676837 -0.459256793773739 475 42.815 42.8088904469611 0.00610955303893443 0.00610955303894237 -1.82351482828326 476 42.7017 42.7264101166509 0.00617752916272254 -0.0247101166508922 -0.322837924381112 477 42.28 42.2743452801533 0.00565471984664048 0.00565471984665587 -1.66354875780833 478 41.922 41.9164143372593 0.00558566274072442 0.00558566274071513 -1.32307038091082 479 42.17 42.1643683121336 0.00563168786645037 0.00563168786644145 0.881966375836146 480 42.1962 42.1905644077463 0.00563559225371849 0.00563559225372617 0.0748328677318842 481 42.3215 42.3435947009786 0.00552367524465091 -0.0220947009786074 0.537124979194506 482 42.3173 42.311818439851 0.00548156014902079 0.00548156014903183 -0.13541248862714 483 42.391 42.3855056192459 0.00549438075413896 0.00549438075413135 0.248196657079541 484 42.463 42.4574931228875 0.00550687711250599 0.00550687711249642 0.241964968729622 485 42.4125 42.4070036445627 0.00549635543730425 0.00549635543731397 -0.203767781761516 486 42.304 42.3262446900114 0.00556117250284429 -0.022244690011381 -0.314320369111986 487 41.813 41.8080241674431 0.0049758325569216 0.00497583255693664 -1.90156452054056 488 41.651 41.6460552269357 0.00494477306426625 0.00494477306425994 -0.607502654599594 489 41.539 41.5340769760101 0.00492302398986871 0.00492302398986 -0.425476311267741 490 41.1575 41.152648828562 0.00485117143800989 0.00485117143802202 -1.40591016914564 491 40.9545 40.9744492769696 0.00498731924238766 -0.0199492769695559 -0.667039387371668

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/1gzo01292718882.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/1gzo01292718882.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/2985k1292718882.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/2985k1292718882.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/31hmn1292718882.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/31hmn1292718882.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/41hmn1292718882.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/41hmn1292718882.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/5c9481292718882.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/19/t1292718784q1c9qm98q0heihq/5c9481292718882.ps (open in new window)

Parameters (Session):

par1 = 5 ;

Parameters (R input):

par1 = 5 ;

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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As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

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