R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(255 + ,280.2 + ,299.9 + ,339.2 + ,374.2 + ,393.5 + ,389.2 + ,381.7 + ,375.2 + ,369 + ,357.4 + ,352.1 + ,346.5 + ,342.9 + ,340.3 + ,328.3 + ,322.9 + ,314.3 + ,308.9 + ,294 + ,285.6 + ,281.2 + ,280.3 + ,278.8 + ,274.5 + ,270.4 + ,263.4 + ,259.9 + ,258 + ,262.7 + ,284.7 + ,311.3 + ,322.1 + ,327 + ,331.3 + ,333.3 + ,321.4 + ,327 + ,320 + ,314.7 + ,316.7 + ,314.4 + ,321.3 + ,318.2 + ,307.2 + ,301.3 + ,287.5 + ,277.7 + ,274.4 + ,258.8 + ,253.3 + ,251 + ,248.4 + ,249.5 + ,246.1 + ,244.5 + ,243.6 + ,244 + ,240.8 + ,249.8 + ,248 + ,259.4 + ,260.5 + ,260.8 + ,261.3 + ,259.5 + ,256.6 + ,257.9 + ,256.5 + ,254.2 + ,253.3 + ,253.8 + ,255.5 + ,257.1 + ,257.3 + ,253.2 + ,252.8 + ,252 + ,250.7 + ,252.2 + ,250 + ,251 + ,253.4 + ,251.2 + ,255.6 + ,261.1 + ,258.9 + ,259.9 + ,261.2 + ,264.7 + ,267.1 + ,266.4 + ,267.7 + ,268.6 + ,267.5 + ,268.5 + ,268.5 + ,270.5 + ,270.9 + ,270.1 + ,269.3 + ,269.8 + ,270.1 + ,264.9 + ,263.7 + ,264.8 + ,263.7 + ,255.9 + ,276.2 + ,360.1 + ,380.5 + ,373.7 + ,369.8 + ,366.6 + ,359.3 + ,345.8 + ,326.2 + ,324.5 + ,328.1 + ,327.5 + ,324.4 + ,316.5 + ,310.9 + ,301.5 + ,291.7 + ,290.4 + ,287.4 + ,277.7 + ,281.6 + ,288 + ,276 + ,272.9 + ,283 + ,283.3 + ,276.8 + ,284.5 + ,282.7 + ,281.2 + ,287.4 + ,283.1 + ,284 + ,285.5 + ,289.2 + ,292.5 + ,296.4 + ,305.2 + ,303.9 + ,311.5 + ,316.3 + ,316.7 + ,322.5 + ,317.1 + ,309.8 + ,303.8 + ,290.3 + ,293.7 + ,291.7 + ,296.5 + ,289.1 + ,288.5 + ,293.8 + ,297.7 + ,305.4 + ,302.7 + ,302.5 + ,303 + ,294.5 + ,294.1 + ,294.5 + ,297.1 + ,289.4 + ,292.4 + ,287.9 + ,286.6 + ,280.5 + ,272.4 + ,269.2 + ,270.6 + ,267.3 + ,262.5 + ,266.8 + ,268.8 + ,263.1 + ,261.2 + ,266 + ,262.5 + ,265.2 + ,261.3 + ,253.7 + ,249.2 + ,239.1 + ,236.4 + ,235.2 + ,245.2 + ,246.2 + ,247.7 + ,251.4 + ,253.3 + ,254.8 + ,250 + ,249.3 + ,241.5 + ,243.3 + ,248 + ,253 + ,252.9 + ,251.5 + ,251.6 + ,253.5 + ,259.8 + ,334.1 + ,448 + ,445.8 + ,445 + ,448.2 + ,438.2 + ,439.8 + ,423.4 + ,410.8 + ,408.4 + ,406.7 + ,405.9 + ,402.7 + ,405.1 + ,399.6 + ,386.5 + ,381.4 + ,375.2 + ,357.7 + ,359 + ,355 + ,352.7 + ,344.4 + ,343.8 + ,338 + ,339 + ,333.3 + ,334.4 + ,328.3 + ,330.7 + ,330 + ,331.6 + ,351.2 + ,389.4 + ,410.9 + ,442.8 + ,462.8 + ,466.9 + ,461.7 + ,439.2 + ,430.3 + ,416.1 + ,402.5 + ,397.3 + ,403.3 + ,395.9 + ,387.8 + ,378.6 + ,377.1 + ,370.4 + ,362 + ,350.3 + ,348.2 + ,344.6 + ,343.5 + ,342.8 + ,347.6 + ,346.6 + ,349.5 + ,342.1 + ,342 + ,342.8 + ,339.3 + ,348.2 + ,333.7 + ,334.7 + ,354 + ,367.7 + ,363.3 + ,358.4 + ,353.1 + ,343.1 + ,344.6 + ,344.4 + ,333.9 + ,331.7 + ,324.3 + ,321.2 + ,322.4 + ,321.7 + ,320.5 + ,312.8 + ,309.7 + ,315.6 + ,309.7 + ,304.6 + ,302.5 + ,301.5 + ,298.8 + ,291.3 + ,293.6 + ,294.6 + ,285.9 + ,297.6 + ,301.1 + ,293.8 + ,297.7 + ,292.9 + ,292.1 + ,287.2 + ,288.2 + ,283.8 + ,299.9 + ,292.4 + ,293.3 + ,300.8 + ,293.7 + ,293.1 + ,294.4 + ,292.1 + ,291.9 + ,282.5 + ,277.9 + ,287.5 + ,289.2 + ,285.6 + ,293.2 + ,290.8 + ,283.1 + ,275 + ,287.8 + ,287.8 + ,287.4 + ,284 + ,277.8 + ,277.6 + ,304.9 + ,294 + ,300.9 + ,324 + ,332.9 + ,341.6 + ,333.4 + ,348.2 + ,344.7 + ,344.7 + ,329.3 + ,323.5 + ,323.2 + ,317.4 + ,330.1 + ,329.2 + ,334.9 + ,315.8 + ,315.4 + ,319.6 + ,317.3 + ,313.8 + ,315.8 + ,311.3) > par1 = '12' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) > nx <- length(x) > x <- ts(x,frequency=par1) > m <- StructTS(x,type='BSM') > m$coef level slope seas epsilon 41.84180972 59.72093058 0.04640952 0.00000000 > m$fitted level slope sea Jan 1 255.0000 0.00000000 0.000000000 Feb 1 279.2950 8.86139690 0.904992414 Mar 1 299.1421 16.41856358 0.757932152 Apr 1 338.5212 31.95031103 0.678772145 May 1 373.5558 34.03705287 0.644234761 Jun 1 392.8655 24.06628863 0.634463817 Jul 1 388.5730 4.86138240 0.627017434 Aug 1 381.0467 -3.52848480 0.653333483 Sep 1 374.5400 -5.54559438 0.660002777 Oct 1 368.3403 -5.98861716 0.659696639 Nov 1 356.7476 -9.78428855 0.652401775 Dec 1 351.4327 -6.75717707 0.667341017 Jan 2 351.9452 -1.94461589 -5.445176078 Feb 2 342.5328 -6.31228648 0.367194458 Mar 2 339.9869 -3.74312233 0.313109816 Apr 2 327.9651 -9.34339359 0.334910657 May 2 322.5404 -6.69280580 0.359624415 Jun 2 313.9436 -7.98095942 0.356428465 Jul 2 308.5588 -6.22433872 0.341217113 Aug 2 293.6792 -12.08087555 0.320828445 Sep 2 285.2417 -9.61554604 0.358279582 Oct 2 280.8293 -6.09484405 0.370722791 Nov 2 279.9535 -2.56326498 0.346454213 Dec 2 278.4598 -1.83958740 0.340170595 Jan 3 278.1172 -0.83721457 -3.617240195 Feb 3 270.1780 -5.22586566 0.222029417 Mar 3 263.1412 -6.45653390 0.258811403 Apr 3 259.6711 -4.43798893 0.228870709 May 3 257.7240 -2.75455349 0.276047697 Jun 3 262.4448 2.29852312 0.255199367 Jul 3 284.3603 15.55970484 0.339684284 Aug 3 311.0647 23.09370822 0.235343858 Sep 3 321.9127 14.81535708 0.187250313 Oct 3 326.7742 8.08624654 0.225791646 Nov 3 331.0649 5.52027119 0.235129156 Dec 3 333.0796 3.15065410 0.220425447 Jan 4 324.9370 -4.43449856 -3.537022311 Feb 4 326.6195 -0.55945388 0.380540113 Mar 4 319.6402 -4.91232147 0.359837209 Apr 4 314.3174 -5.18951071 0.382613030 May 4 316.2325 -0.39171470 0.467460794 Jun 4 314.0849 -1.57762565 0.315088247 Jul 4 320.8548 4.06039390 0.445213930 Aug 4 317.8273 -0.72691152 0.372652096 Sep 4 306.8672 -7.63874020 0.332795533 Oct 4 300.8945 -6.51342098 0.405461582 Nov 4 287.1609 -11.39029714 0.339056078 Dec 4 277.2685 -10.37873712 0.431473466 Jan 5 278.0453 -2.87719956 -3.645296127 Feb 5 258.5886 -13.52932453 0.211396037 Mar 5 253.0529 -8.11848847 0.247052079 Apr 5 250.8392 -4.13408159 0.160760454 May 5 248.0850 -3.20300939 0.314995955 Jun 5 249.4279 -0.13530048 0.072121830 Jul 5 245.8613 -2.45094171 0.238724246 Aug 5 244.2367 -1.89327175 0.263325732 Sep 5 243.4887 -1.12034801 0.111305016 Oct 5 243.7292 -0.20197859 0.270849267 Nov 5 240.6626 -2.13528135 0.137420974 Dec 5 249.5588 5.30805410 0.241210071 Jan 6 250.2992 2.23509802 -2.299177696 Feb 6 259.1636 6.53298992 0.236423910 Mar 6 260.2790 2.87088063 0.221026464 Apr 6 260.5789 1.13739102 0.221072233 May 6 260.9723 0.63573430 0.327692388 Jun 6 259.3490 -0.88758140 0.150996032 Jul 6 256.3116 -2.33732556 0.288444112 Aug 6 257.5493 0.07353156 0.350682008 Sep 6 256.3637 -0.77557484 0.136295666 Oct 6 253.8111 -1.97394085 0.388925268 Nov 6 253.1836 -1.06591777 0.116410847 Dec 6 253.4534 -0.16539174 0.346601768 Jan 7 258.1650 3.11604450 -2.664956346 Feb 7 256.8748 0.24154535 0.225169742 Mar 7 257.0929 0.22567431 0.207130645 Apr 7 253.0504 -2.65019932 0.149612516 May 7 252.4711 -1.25482843 0.328887518 Jun 7 251.8460 -0.83047329 0.153968466 Jul 7 250.4913 -1.18374865 0.208692475 Aug 7 251.8599 0.53622306 0.340075382 Sep 7 249.9016 -1.14477723 0.098378829 Oct 7 250.6333 0.11976145 0.366653608 Nov 7 253.2971 1.83413991 0.102949933 Dec 7 250.9693 -0.96965798 0.230737090 Jan 8 257.7683 4.25718761 -2.168292398 Feb 8 260.9229 3.53459178 0.177119005 Mar 8 258.7089 -0.34282275 0.191066024 Apr 8 259.7671 0.60055220 0.132916047 May 8 260.8976 0.95738726 0.302433666 Jun 8 264.5276 2.75719089 0.172416827 Jul 8 266.9602 2.53863669 0.139762095 Aug 8 266.0749 0.23279733 0.325092877 Sep 8 267.6129 1.11175975 0.087117479 Oct 8 268.3070 0.83053118 0.292951945 Nov 8 267.3537 -0.37087764 0.146319621 Dec 8 268.3483 0.54840995 0.151681662 Jan 9 270.6180 1.70635159 -2.118046110 Feb 9 270.2715 0.35632185 0.228510309 Mar 9 270.7336 0.42760314 0.166415282 Apr 9 269.9807 -0.36687886 0.119342870 May 9 269.0450 -0.74967442 0.255034660 Jun 9 269.6389 0.15460919 0.161112644 Jul 9 269.9260 0.24375822 0.174047294 Aug 9 264.6568 -3.46669133 0.243180239 Sep 9 263.5950 -1.84810412 0.105021965 Oct 9 264.4676 -0.01687000 0.332366997 Nov 9 263.5886 -0.59716134 0.111378332 Dec 9 255.8457 -5.40482442 0.054298090 Jan 10 277.4853 12.78436815 -1.285319120 Feb 10 359.3225 58.31670474 0.777493230 Mar 10 380.5936 33.37096653 -0.093551187 Apr 10 373.6881 6.27932951 0.011881656 May 10 369.3564 -0.85787021 0.443585280 Jun 10 366.2414 -2.37618927 0.358566503 Jul 10 358.8678 -5.73794009 0.432194232 Aug 10 345.4234 -10.92203784 0.376561703 Sep 10 326.0027 -16.63910333 0.197289015 Oct 10 323.8159 -6.91687208 0.684059358 Nov 10 327.3577 0.11890756 0.742344088 Dec 10 327.4723 0.11603296 0.027711505 Jan 11 329.1971 1.19781115 -4.797134927 Feb 11 315.6198 -8.56551172 0.880212963 Mar 11 310.4787 -6.26117316 0.421276569 Apr 11 301.4340 -8.13263041 0.065964284 May 11 291.3182 -9.46594497 0.381796938 Jun 11 289.9833 -3.99891609 0.416744204 Jul 11 286.9650 -3.33953863 0.434999167 Aug 11 277.2376 -7.63465547 0.462442491 Sep 11 281.4393 0.32398369 0.160660270 Oct 11 287.4602 4.15455648 0.539784006 Nov 11 275.5001 -6.68106686 0.499857372 Dec 11 272.8875 -3.94672434 0.012513334 Jan 12 286.7635 8.03442117 -3.763505491 Feb 12 282.6223 -0.02508878 0.677728014 Mar 12 276.4752 -4.14207748 0.324830353 Apr 12 284.2756 3.88404650 0.224393618 May 12 282.5810 0.13505995 0.119033332 Jun 12 280.9101 -1.07869007 0.289912951 Jul 12 286.7744 3.58769168 0.625611466 Aug 12 282.9394 -1.40109383 0.160593150 Sep 12 284.0478 0.28556335 -0.047834347 Oct 12 284.7597 0.57208672 0.740302381 Nov 12 288.6983 2.83476837 0.501746039 Dec 12 292.7859 3.67646795 -0.285935849 Jan 13 299.6422 5.81348186 -3.242160307 Feb 13 304.3696 5.09357063 0.830397717 Mar 13 303.8694 1.33388962 0.030624343 Apr 13 311.1278 5.31409715 0.372227168 May 13 316.1362 5.10875533 0.163805169 Jun 13 316.6243 2.00441269 0.075731717 Jul 13 321.7143 4.07749821 0.785675325 Aug 13 317.0844 -1.77259835 0.015632207 Sep 13 309.8882 -5.41642396 -0.088214040 Oct 13 303.1086 -6.33231766 0.691417221 Nov 13 289.8803 -10.96548875 0.419708517 Dec 13 293.8518 -0.93484235 -0.151798199 Jan 14 294.8556 0.36775416 -3.155633466 Feb 14 295.5438 0.58038624 0.956219488 Mar 14 289.2615 -4.02986196 -0.161463887 Apr 14 288.1086 -2.09764001 0.391379294 May 14 293.4711 2.91208347 0.328929247 Jun 14 297.7405 3.82367759 -0.040477783 Jul 14 304.4989 5.79470233 0.901132140 Aug 14 302.7260 0.71217092 -0.026049217 Sep 14 302.6082 0.15471852 -0.108217758 Oct 14 302.1140 -0.28115485 0.886029248 Nov 14 294.3935 -5.27766474 0.106503258 Dec 14 294.2096 -1.85819917 -0.109648433 Jan 15 297.5815 1.65502217 -3.081519352 Feb 15 296.0427 -0.46668173 1.057263869 Mar 15 289.6472 -4.44783583 -0.247184191 Apr 15 292.0393 0.14463867 0.360650463 May 15 287.6573 -2.89427459 0.242703673 Jun 15 286.7251 -1.57691143 -0.125106447 Jul 15 279.5660 -5.32496051 0.934043309 Aug 15 272.4550 -6.52412303 -0.054995742 Sep 15 269.3122 -4.25382401 -0.112176785 Oct 15 269.5234 -1.25580530 1.076612006 Nov 15 267.2845 -1.91590440 0.015544725 Dec 15 262.7432 -3.67773291 -0.243233142 Jan 16 269.6000 3.39702186 -2.800045332 Feb 16 267.6596 -0.15173814 1.140410316 Mar 16 263.5586 -2.80255322 -0.458608367 Apr 16 260.7686 -2.79411830 0.431378744 May 16 265.7518 2.42558065 0.248233440 Jun 16 262.6426 -1.28947539 -0.142639789 Jul 16 264.1899 0.61463502 1.010149077 Aug 16 261.4446 -1.64068204 -0.144577355 Sep 16 253.9842 -5.54714411 -0.284192907 Oct 16 248.1253 -5.75639400 1.074676219 Nov 16 239.0350 -7.99428340 0.065029291 Dec 16 236.7576 -4.15874756 -0.357604451 Jan 17 237.7535 -0.69779070 -2.553498195 Feb 17 243.9166 3.86713891 1.283361025 Mar 17 246.6378 3.09822928 -0.437835181 Apr 17 247.4570 1.56879929 0.242953783 May 17 251.0058 2.89731899 0.394196131 Jun 17 253.5192 2.63965599 -0.219162217 Jul 17 253.7972 1.05483935 1.002760777 Aug 17 250.1059 -2.13022163 -0.105923127 Sep 17 249.5632 -1.06485478 -0.263225726 Oct 17 240.4188 -6.48711153 1.081243145 Nov 17 243.1540 -0.29823612 0.145982039 Dec 17 248.3483 3.38588600 -0.348328433 Jan 18 255.6967 6.04582740 -2.696696870 Feb 18 251.7148 -0.63024712 1.185237520 Mar 18 251.8876 -0.09156552 -0.387591256 Apr 18 251.4194 -0.34428528 0.180630993 May 18 253.1147 1.02394571 0.385323209 Jun 18 259.9591 4.92900149 -0.159077741 Jul 18 332.2038 50.09371925 1.896188924 Aug 18 447.4830 93.82908248 0.517006483 Sep 18 447.2155 30.69571112 -1.415535081 Oct 18 444.4075 8.21608552 0.592504868 Nov 18 448.0995 5.18077515 0.100527635 Dec 18 438.7945 -4.53344507 -0.594547181 Jan 19 442.0828 0.71604674 -2.282792054 Feb 19 422.4656 -12.82815183 0.934408549 Mar 19 411.1909 -11.78645591 -0.390855509 Apr 19 408.0309 -5.99952952 0.369112574 May 19 405.8203 -3.45827749 0.879695570 Jun 19 406.9126 -0.40581553 -1.012599226 Jul 19 402.7216 -2.94494679 -0.021598719 Aug 19 403.1450 -0.68542077 1.954977022 Sep 19 400.5349 -1.97651502 -0.934929461 Oct 19 386.1079 -10.32867526 0.392119636 Nov 19 380.9796 -6.84037258 0.420429026 Dec 19 375.9845 -5.60313689 -0.784491084 Jan 20 359.5470 -12.87319554 -1.846966987 Feb 20 357.9025 -5.39019361 1.097497780 Mar 20 355.4604 -3.41374328 -0.460407876 Apr 20 352.3554 -3.20665197 0.344576268 May 20 343.6715 -6.87961406 0.728515219 Jun 20 344.5957 -1.64586106 -0.795688257 Jul 20 338.1613 -4.85747756 -0.161296074 Aug 20 337.0156 -2.36800228 1.984362083 Sep 20 333.9637 -2.82673837 -0.663664068 Oct 20 334.0465 -0.87525927 0.353496476 Nov 20 328.0138 -4.33414003 0.286230782 Dec 20 331.1397 0.66689814 -0.439736265 Jan 21 332.1197 0.87692456 -2.119687955 Feb 21 330.5923 -0.72595429 1.007655376 Mar 21 351.4113 13.71481145 -0.211284443 Apr 21 388.6438 29.48627398 0.756185374 May 21 410.4941 24.36655212 0.405919384 Jun 21 443.4006 30.09306376 -0.600580270 Jul 21 463.1805 23.17725832 -0.380500514 Aug 21 465.1710 8.96978115 1.729037956 Sep 21 462.5679 1.20920428 -0.867948542 Oct 21 439.0109 -15.39905433 0.189092302 Nov 21 430.0497 -11.08219964 0.250255003 Dec 21 416.5329 -12.71407402 -0.432900179 Jan 22 404.3370 -12.36646615 -1.837038690 Feb 22 396.4859 -9.35514420 0.814105409 Mar 22 403.7544 1.78486724 -0.454443900 Apr 22 395.0921 -5.22031250 0.807940676 May 22 387.6673 -6.69812454 0.132720439 Jun 22 379.1725 -7.90268230 -0.572528792 Jul 22 377.1177 -3.98180487 -0.017680779 Aug 22 368.6628 -6.98095107 1.737228381 Sep 22 362.3557 -6.52913996 -0.355671795 Oct 22 350.3043 -10.23180097 -0.004308736 Nov 22 347.7730 -5.06912232 0.426978516 Dec 22 344.9714 -3.54945982 -0.371430004 Jan 23 345.3443 -0.91886749 -1.844271880 Feb 23 342.4082 -2.26454575 0.391758545 Mar 23 347.7798 2.85172089 -0.179833223 Apr 23 345.8222 -0.37266507 0.777773770 May 23 349.2570 2.17938936 0.242998881 Jun 23 342.9274 -3.52475834 -0.827351430 Jul 23 341.9069 -1.84586314 0.093065965 Aug 23 341.0843 -1.15989880 1.715705692 Sep 23 339.5075 -1.43939929 -0.207480905 Oct 23 348.1983 5.35200434 0.001715831 Nov 23 333.5652 -8.04470726 0.134776833 Dec 23 335.0030 -1.69046980 -0.302965813 Jan 24 355.4117 13.12872291 -1.411713469 Feb 24 367.4968 12.43231034 0.203203556 Mar 24 363.6316 1.51465956 -0.331628825 Apr 24 357.8520 -3.37516553 0.547966703 May 24 352.6938 -4.57017724 0.406204115 Jun 24 344.0153 -7.32389257 -0.915304252 Jul 24 344.4141 -2.14730691 0.185934468 Aug 24 342.6675 -1.87865749 1.732460015 Sep 24 334.5152 -6.08403600 -0.615204422 Oct 24 331.1858 -4.23754566 0.514225397 Nov 24 324.2382 -6.05392334 0.061783423 Dec 24 321.8858 -3.57381786 -0.685753456 Jan 25 323.8139 0.11516728 -1.413930225 Feb 25 321.2709 -1.65903687 0.429091970 Mar 25 320.7059 -0.92624195 -0.205921070 Apr 25 312.3298 -5.91986262 0.470207219 May 25 309.1261 -4.09966323 0.573851576 Jun 25 316.5198 3.60314047 -0.919768155 Jul 25 309.7099 -3.37605997 -0.009859618 Aug 25 302.7925 -5.74956554 1.807480351 Sep 25 303.0943 -1.69364947 -0.594334433 Oct 25 300.9077 -2.02406393 0.592285909 Nov 25 298.7842 -2.09069508 0.015774860 Dec 25 292.1667 -5.12353428 -0.866706268 Jan 26 294.8585 0.11580217 -1.258490647 Feb 26 294.2430 -0.37240041 0.357002367 Mar 26 286.0304 -5.62309713 -0.130368416 Apr 26 296.9203 5.44440425 0.679695992 May 26 300.8550 4.43284676 0.244958978 Jun 26 294.6877 -2.67063085 -0.887709855 Jul 26 297.5334 1.02620038 0.166629564 Aug 26 291.3110 -3.83157406 1.588992858 Sep 26 292.6293 -0.38023525 -0.529319799 Oct 26 286.6999 -4.09918830 0.500097468 Nov 26 287.9871 -0.48984940 0.212926643 Dec 26 284.8569 -2.25861185 -1.056937560 Jan 27 300.8592 9.98181528 -0.959159277 Feb 27 291.9926 -2.60338099 0.407377399 Mar 27 293.7456 0.31378356 -0.445605988 Apr 27 300.0897 4.35511403 0.710269599 May 27 293.3977 -3.04636209 0.302308070 Jun 27 294.1001 -0.53445189 -1.000108097 Jul 27 294.0811 -0.18904379 0.318887191 Aug 27 290.6995 -2.32839809 1.400487256 Sep 27 292.2568 0.27547994 -0.356838902 Oct 27 282.2457 -6.61775531 0.254335875 Nov 27 277.5456 -5.33288971 0.354433954 Dec 27 288.7403 5.73831135 -1.240290242 Jan 28 289.7139 2.54486797 -0.513923399 Feb 28 285.3458 -2.07170591 0.254152710 Mar 28 293.6917 4.90349077 -0.491705119 Apr 28 289.9683 -0.87744495 0.831674850 May 28 282.9596 -4.98500004 0.140433276 Jun 28 276.0495 -6.27478958 -1.049503530 Jul 28 287.1867 5.39197751 0.613265390 Aug 28 286.6230 1.40133671 1.177041489 Sep 28 287.5300 1.07015598 -0.130036103 Oct 28 283.7621 -2.17159810 0.237865099 Nov 28 277.8570 -4.67289975 -0.056988968 Dec 28 278.6848 -0.98846009 -1.084786957 Jan 29 304.8376 17.20050401 0.062440211 Feb 29 294.3585 -1.28701324 -0.358472545 Mar 29 301.1865 4.14601039 -0.286547872 Apr 29 322.8196 15.86329405 1.180355531 May 29 332.7389 11.88153494 0.161082435 Jun 29 343.0924 10.85782233 -1.492387045 Jul 29 333.0015 -3.17750354 0.398513627 Aug 29 346.8485 8.22879018 1.351523645 Sep 29 344.8950 1.40666599 -0.194989679 Oct 29 344.3660 0.10980890 0.333965263 Nov 29 329.5760 -9.87145676 -0.276035446 Dec 29 325.1277 -6.23923803 -1.627666556 Jan 30 322.3188 -3.94054347 0.881151747 Feb 30 317.8180 -4.31481330 -0.418017575 Mar 30 330.5538 7.09950441 -0.453801844 Apr 30 328.0819 0.68663693 1.118107179 May 30 334.7252 4.67658630 0.174775248 Jun 30 317.0850 -10.27311331 -1.285022244 Jul 30 315.2846 -4.59699429 0.115415379 Aug 30 317.9806 0.28888891 1.619414850 Sep 30 317.5453 -0.19625040 -0.245329909 Oct 30 313.1913 -2.98169423 0.608662188 Nov 30 316.0788 0.94966243 -0.278780417 Dec 30 313.0235 -1.73255920 -1.723508892 > m$resid Jan Feb Mar Apr May 1 0.0000000000 1.8334035452 0.9212831001 1.9969487936 0.2698531305 2 0.7036657409 -0.5258542361 0.3239174689 -0.7224613265 0.3428884410 3 0.1378094897 -0.5477174889 -0.1566899124 0.2606339562 0.2177962126 4 -1.0213156735 0.4897288852 -0.5569367251 -0.0358047310 0.6207490361 5 0.9993745198 -1.3547485773 0.6943803341 0.5147747314 0.1204672464 6 -0.4067268980 0.5486917816 -0.4709264383 -0.2239883830 -0.0649081065 7 0.4323955430 -0.3679084752 -0.0020439713 -0.3716245212 0.1805451569 8 0.6865158951 -0.0926544146 -0.4999238800 0.1219096417 0.0461706200 9 0.1517135567 -0.1733452924 0.0091985888 -0.1026717428 -0.0495297032 10 2.3785107849 5.8526979903 -3.2214153987 -3.5011631777 -0.9234774710 11 0.1412365471 -1.2560565564 0.2977426489 -0.2418612064 -0.1725161989 12 1.5622348860 -1.0375950988 -0.5321960259 1.0372931024 -0.4850754370 13 0.2783482342 -0.0927373425 -0.4861860746 0.5144124391 -0.0265687065 14 0.1695112092 0.0274044412 -0.5963551767 0.2497319042 0.6481923512 15 0.4568369208 -0.2735656743 -0.5151029891 0.5935760104 -0.3931925103 16 0.9193547453 -0.4577331638 -0.3430430268 0.0010902465 0.6753499734 17 0.4494945231 0.5889895573 -0.0995203329 -0.1976915537 0.1718888537 18 0.3452952212 -0.8616181625 0.0697304114 -0.0326673434 0.1770252758 19 0.6811684225 -1.7484465062 0.1348569162 0.7480653860 0.3287908008 20 -0.9430137760 0.9662015295 0.2558885924 0.0267714029 -0.4752087243 21 0.0272343807 -0.2070020653 1.8697357550 2.0389160996 -0.6623848616 22 0.0450623926 0.3889592257 1.4424282871 -0.9056598228 -0.1911962562 23 0.3409372194 -0.1738413462 0.6624835137 -0.4168803297 0.3301766770 24 1.9202363909 -0.0899780298 -1.4137092072 -0.6322316746 -0.1546055415 25 0.4779226868 -0.2292585160 0.0948896366 -0.6456793023 0.2354878413 26 0.6786680789 -0.0630911856 -0.6799168785 1.4310968471 -0.1308690456 27 1.5853188603 -1.6265622556 0.3777461411 0.5225905700 -0.9575507199 28 -0.4135477075 -0.5967170993 0.9032207470 -0.7475713854 -0.5314032041 29 2.3551967226 -2.3898005875 0.7035190688 1.5152988572 -0.5151258449 30 0.2976178543 -0.0483836988 1.4780185392 -0.8293538961 0.5161828726 Jun Jul Aug Sep Oct 1 -1.2901383949 -2.4851116550 -1.0856541375 -0.2610154262 -0.0573274698 2 -0.1666829898 0.2273072771 -0.7578398735 0.3190154200 0.4555813953 3 0.6538589520 1.7160029825 0.9749053021 -1.0712246325 -0.8707517950 4 -0.1534555277 0.7295626906 -0.6194806997 -0.8943956408 0.1456171246 5 0.3969593114 -0.2996452842 0.0721628881 0.1000168924 0.1188376713 6 -0.1971163834 -0.1875977545 0.3119666280 -0.1098749844 -0.1550694350 7 0.0549114602 -0.0457140487 0.2225655663 -0.2175226575 0.1636322301 8 0.2328944776 -0.0282810522 -0.2983772609 0.1137383754 -0.0363911842 9 0.1170143577 0.0115359418 -0.4801348255 0.2094463613 0.2369630739 10 -0.1964707364 -0.4350127809 -0.6708259613 -0.7397924302 1.2580642640 11 0.7074348484 0.0853238885 -0.5557911979 1.0298536925 0.4956792149 12 -0.1570596116 0.6038330102 -0.6455524262 0.2182546661 0.0370763677 13 -0.4017029738 0.2682587163 -0.7570067014 -0.4715136823 -0.1185174739 14 0.1179606054 0.2550519980 -0.6576832245 -0.0721347469 -0.0564024354 15 0.1704672792 -0.4850002366 -0.1551724953 0.2937783474 0.3879467215 16 -0.4807296282 0.2463932626 -0.2918396599 -0.5054990473 -0.0270771664 17 -0.0333416854 -0.2050764223 -0.4121492007 0.1378592542 -0.7016463823 18 0.5053155619 5.8443473246 5.6593877688 -8.1695050947 -2.9088913499 19 0.3949895468 -0.3285654325 0.2923843105 -0.1670685664 -1.0807803297 20 0.6772491098 -0.4155855065 0.3221399107 -0.0593608006 0.2525240059 21 0.7410119524 -0.8949102325 -1.8384578627 -1.0042247067 -2.1491314165 22 -0.1558699895 0.5073643715 -0.3880916913 0.0584647205 -0.4791294761 23 -0.7381173418 0.2172502478 0.0887642806 -0.0361675936 0.8788170829 24 -0.3563308467 0.6698539056 0.0347634276 -0.5441795575 0.2389383998 25 0.9967423180 -0.9031135544 -0.3071333107 0.5248391101 -0.0427560789 26 -0.9191888080 0.4783726241 -0.6285994426 0.4466063887 -0.4812374243 27 0.3250404575 0.0446960577 -0.2768339421 0.3369442789 -0.8919933816 28 -0.1668982241 1.5096881436 -0.5163916798 -0.0428551109 -0.4194868937 29 -0.1324678314 -1.8161814543 1.4759822067 -0.8827897871 -0.1678147857 30 -1.9344802986 0.7344940038 0.6322365866 -0.0627775348 -0.3604393984 Nov Dec 1 -0.4911626375 0.3917104267 2 0.4569889306 0.0936444887 3 -0.3320391953 -0.3066317278 4 -0.6310719243 0.1308984866 5 -0.2501712438 0.9632019824 6 0.1174991881 0.1165348453 7 0.2218427040 -0.3628430758 8 -0.1554639372 0.1189703239 9 -0.0750905336 -0.6222120064 10 0.9104401446 -0.0003720492 11 -1.4021450209 0.3539118507 12 0.2927939886 0.1089478845 13 -0.5995377619 1.2984037883 14 -0.6465533161 0.4426469464 15 -0.0854173446 -0.2280762795 16 -0.2895842068 0.4965447374 17 0.8008430012 0.4769585421 18 -0.3927699479 -1.2576713033 19 0.4513869100 0.1601852461 20 -0.4475795392 0.6474994300 21 0.5586015086 -0.2112873123 22 0.6680516228 0.1967613139 23 -1.7335389795 0.8227357642 24 -0.2350402537 0.3211219989 25 -0.0086221246 -0.3926910322 26 0.4670525307 -0.2290190656 27 0.1662635415 1.4334955658 28 -0.3236732449 0.4770584847 29 -1.2915995573 0.4702945139 30 0.5087288521 -0.3472878671 > 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 > postscript(file="/var/www/rcomp/tmp/1mrvw1321461521.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > postscript(file="/var/www/rcomp/tmp/2ww7q1321461521.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > postscript(file="/var/www/rcomp/tmp/3homs1321461521.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > 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() null device 1 > postscript(file="/var/www/rcomp/tmp/45svs1321461521.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5hc1x1321461521.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > hist(m$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() null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/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="/var/www/rcomp/tmp/6jjt61321461522.tab") > > try(system("convert tmp/1mrvw1321461521.ps tmp/1mrvw1321461521.png",intern=TRUE)) character(0) > try(system("convert tmp/2ww7q1321461521.ps tmp/2ww7q1321461521.png",intern=TRUE)) character(0) > try(system("convert tmp/3homs1321461521.ps tmp/3homs1321461521.png",intern=TRUE)) character(0) > try(system("convert tmp/45svs1321461521.ps tmp/45svs1321461521.png",intern=TRUE)) character(0) > try(system("convert tmp/5hc1x1321461521.ps tmp/5hc1x1321461521.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.250 0.200 6.464