ws8

*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: Tue, 01 Dec 2009 10:50:31 -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/01/t1259689891oxec2lt1smv9nue.htm/, Retrieved Tue, 01 Dec 2009 18:51:38 +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/01/t1259689891oxec2lt1smv9nue.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 «

325412 326011 328282 317480 317539 313737 312276 309391 302950 300316 304035 333476 337698 335932 323931 313927 314485 313218 309664 302963 298989 298423 310631 329765 335083 327616 309119 295916 291413 291542 284678 276475 272566 264981 263290 296806 303598 286994 276427 266424 267153 268381 262522 255542 253158 243803 250741 280445 285257 270976 261076 255603 260376 263903 264291 263276 262572 256167 264221 293860 300713 287224

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 2 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 Structural Time Series Model t Observed Level Slope Seasonal Stand. Residuals 1 325412 325412 0 0 0 2 326011 325942.550841046 27.7527563550360 68.4491589535562 0.0495217931639672 3 328282 327718.720947531 76.5255332056774 563.279052468835 0.251364284016571 4 317480 319986.258518802 7.48005821959097 -2506.25851880216 -1.17182663707953 5 317539 317443.820704185 -5.78795037702842 95.1792958145417 -0.382385070780442 6 313737 314384.460827008 -22.9290117275542 -647.460827007662 -0.457691395941157 7 312276 312519.657431044 -34.0127038343482 -243.657431043558 -0.276031371176660 8 309391 309980.391879649 -49.2462602436357 -589.391879649354 -0.375443784236939 9 302950 304397.933526114 -82.6566969766221 -1447.93352611425 -0.82922368442539 10 300316 300840.562711304 -103.476525562518 -524.562711303572 -0.520727406257012 11 304035 303054.478701094 -89.6800411153306 980.52129890612 0.347285143547759 12 333476 326654.123083469 50.5189556438265 6821.87691653061 3.55004922769262 13 337698 335235.919206305 -266.862225657771 2462.08079369462 1.45510683699584 14 335932 336715.200068716 -242.484768370612 -783.200068715771 0.241364074838444 15 323931 326237.26315566 -433.235918536539 -2306.26315566009 -1.45975595457309 16 313927 318390.442015713 -507.018859113401 -4463.44201571332 -1.10617165519554 17 314485 314626.291099368 -522.396857989932 -141.291099368494 -0.488189608088228 18 313218 313748.761252682 -523.648132440838 -530.761252681949 -0.0532020740281788 19 309664 310805.376437261 -532.588714541077 -1141.37643726096 -0.362366830012397 20 302963 304558.933564481 -555.255229640237 -1595.93356448105 -0.855544881056838 21 298989 300238.041429651 -570.987028556055 -1249.04142965143 -0.563874815798923 22 298423 299128.510390822 -573.350834141211 -705.510390822258 -0.0806688149030882 23 310631 310613.566440552 -528.009733379629 17.4335594475797 1.80596068903270 24 329765 322025.222928121 -539.454475321985 7739.77707187923 1.78781619906444 25 335083 329559.115401028 -631.82025307306 5523.88459897229 1.25528891756047 26 327616 326666.588822281 -644.617825091323 949.411177718565 -0.329645300284093 27 309119 314118.819384524 -794.790093684242 -4999.81938452365 -1.71829631337343 28 295916 303114.825186792 -892.576431540558 -7198.8251867916 -1.51571341892716 29 291413 294177.456320278 -936.38099634766 -2764.45632027818 -1.20466977238556 30 291542 291407.589022158 -942.811519159777 134.410977841569 -0.274670469893185 31 284678 285795.125263775 -957.554687138183 -1117.12526377512 -0.699316228857779 32 276475 278771.405241583 -978.141342447736 -2296.4052415833 -0.908305506633994 33 272566 274508.135275656 -990.302102731672 -1942.13527565565 -0.491951414355052 34 264981 270422.713778753 -1001.49868001539 -5441.71377875314 -0.463557031641652 35 263290 267626.089017881 -1005.31407252620 -4336.08901788113 -0.268634185383439 36 296806 283793.078293823 -1034.22825909059 13012.9217061774 2.57470227497034 37 303598 293129.320970829 -1080.62890205628 10468.6790291707 1.57351518540293 38 286994 285471.127444624 -1103.64061072822 1522.87255537598 -0.970935668730854 39 276427 279858.112439805 -1144.26277097603 -3431.11243980523 -0.657801796744838 40 266424 273542.62937679 -1188.01010664923 -7118.62937678974 -0.766155339360943 41 267153 270130.176656009 -1200.75931559783 -2977.17665600925 -0.332625262009254 42 268381 267359.699037066 -1206.72687033244 1021.30096293444 -0.235117805719063 43 262522 262992.919536849 -1216.59631580056 -470.919536849454 -0.473299442041557 44 255542 257929.397263980 -1228.70437671734 -2387.39726398050 -0.576123204837344 45 253158 254454.899598956 -1236.03022317791 -1296.89959895595 -0.336340294217171 46 243803 250362.364671481 -1244.14280049282 -6559.36467148068 -0.427674492397063 47 250741 257031.440444633 -1234.21333799261 -6290.44044463284 1.18382262104702 48 280445 266336.422067546 -1246.87889199199 14108.5779324541 1.57987078392883 49 285257 270928.060782321 -1256.80004007362 14328.9392176792 0.878027098654857 50 270976 268845.370561896 -1259.16311300585 2130.62943810352 -0.122374520755582 51 261076 264450.422250399 -1280.71886264754 -3374.42225039899 -0.460536676492489 52 255603 262408.423617773 -1286.28569560455 -6805.42361777327 -0.112765499690225 53 260376 262351.837292276 -1279.31811543432 -1975.83729227595 0.183644742211955 54 263903 261637.353775415 -1277.03579837621 2265.64622458499 0.0845747778931377 55 264291 262485.069912478 -1270.19665558059 1805.93008752211 0.318263581732331 56 263276 263710.672990517 -1262.7174509006 -434.672990517124 0.373832364138744 57 262572 263126.060137877 -1260.78421610747 -554.060137877382 0.101553242562512 58 256167 264490.021168332 -1254.91654979578 -8323.02116833202 0.392855592228209 59 264221 270948.083393656 -1248.20419905592 -6727.08339365612 1.15377719506950 60 293860 278477.38456098 -1253.60663937016 15382.6154390202 1.31483654014780 61 300713 284007.174677601 -1256.08760761612 16705.8253223985 1.01617355692354 62 287224 284283.511451435 -1252.05678304184 2940.48854856494 0.227438010041143

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/1qq0d1259689828.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/1qq0d1259689828.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/2ykzu1259689828.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/2ykzu1259689828.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/3rm9b1259689828.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/3rm9b1259689828.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/4hvwo1259689828.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/4hvwo1259689828.ps (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/5f5f61259689828.png (open in new window) http://www.freestatistics.org/blog/date/2009/Dec/01/t1259689891oxec2lt1smv9nue/5f5f61259689828.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$resid) myfit <- mylevel+myseas mylagmax <- nx/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(mylevel,na.action=na.pass,lag.max = mylagmax,main='Level') acf(myseas,na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(myresid,na.action=na.pass,lag.max = mylagmax,main='Standardized Residals') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(mylevel,main='Level') spectrum(myseas,main='Seasonal') spectrum(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(mylevel,main='Level') cpgram(myseas,main='Seasonal') cpgram(myresid,main='Standardized Residals') par(op) dev.off() bitmap(file='test1.png') plot(as.numeric(m$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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