R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-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(235.1 + ,280.7 + ,264.6 + ,240.7 + ,201.4 + ,240.8 + ,241.1 + ,223.8 + ,206.1 + ,174.7 + ,203.3 + ,220.5 + ,299.5 + ,347.4 + ,338.3 + ,327.7 + ,351.6 + ,396.6 + ,438.8 + ,395.6 + ,363.5 + ,378.8 + ,357 + ,369 + ,464.8 + ,479.1 + ,431.3 + ,366.5 + ,326.3 + ,355.1 + ,331.6 + ,261.3 + ,249 + ,205.5 + ,235.6 + ,240.9 + ,264.9 + ,253.8 + ,232.3 + ,193.8 + ,177 + ,213.2 + ,207.2 + ,180.6 + ,188.6 + ,175.4 + ,199 + ,179.6 + ,225.8 + ,234 + ,200.2 + ,183.6 + ,178.2 + ,203.2 + ,208.5 + ,191.8 + ,172.8 + ,148 + ,159.4 + ,154.5 + ,213.2 + ,196.4 + ,182.8 + ,176.4 + ,153.6 + ,173.2 + ,171 + ,151.2 + ,161.9 + ,157.2 + ,201.7 + ,236.4 + ,356.1 + ,398.3 + ,403.7 + ,384.6 + ,365.8 + ,368.1 + ,367.9 + ,347 + ,343.3 + ,292.9 + ,311.5 + ,300.9 + ,366.9 + ,356.9 + ,329.7 + ,316.2 + ,269 + ,289.3 + ,266.2 + ,253.6 + ,233.8 + ,228.4 + ,253.6 + ,260.1 + ,306.6 + ,309.2 + ,309.5 + ,271 + ,279.9 + ,317.9 + ,298.4 + ,246.7 + ,227.3 + ,209.1 + ,259.9 + ,266 + ,320.6 + ,308.5 + ,282.2 + ,262.7 + ,263.5 + ,313.1 + ,284.3 + ,252.6 + ,250.3 + ,246.5 + ,312.7 + ,333.2 + ,446.4 + ,511.6 + ,515.5 + ,506.4 + ,483.2 + ,522.3 + ,509.8 + ,460.7 + ,405.8 + ,375 + ,378.5 + ,406.8 + ,467.8 + ,469.8 + ,429.8 + ,355.8 + ,332.7 + ,378 + ,360.5 + ,334.7 + ,319.5 + ,323.1 + ,363.6 + ,352.1 + ,411.9 + ,388.6 + ,416.4 + ,360.7 + ,338 + ,417.2 + ,388.4 + ,371.1 + ,331.5 + ,353.7 + ,396.7 + ,447 + ,533.5 + ,565.4 + ,542.3 + ,488.7 + ,467.1 + ,531.3 + ,496.1 + ,444 + ,403.4 + ,386.3 + ,394.1 + ,404.1 + ,462.1 + ,448.1 + ,432.3 + ,386.3 + ,395.2 + ,421.9 + ,382.9 + ,384.2 + ,345.5 + ,323.4 + ,372.6 + ,376 + ,462.7 + ,487 + ,444.2 + ,399.3 + ,394.9 + ,455.4 + ,414 + ,375.5 + ,347 + ,339.4 + ,385.8 + ,378.8 + ,451.8 + ,446.1 + ,422.5 + ,383.1 + ,352.8 + ,445.3 + ,367.5 + ,355.1 + ,326.2 + ,319.8 + ,331.8 + ,340.9 + ,394.1 + ,417.2 + ,369.9 + ,349.2 + ,321.4 + ,405.7 + ,342.9 + ,316.5 + ,284.2 + ,270.9 + ,288.8 + ,278.8 + ,324.4 + ,310.9 + ,299 + ,273 + ,279.3 + ,359.2 + ,305 + ,282.1 + ,250.3 + ,246.5 + ,257.9 + ,266.5 + ,315.9 + ,318.4 + ,295.4 + ,266.4 + ,245.8 + ,362.8 + ,324.9 + ,294.2 + ,289.5 + ,295.2 + ,290.3 + ,272 + ,307.4 + ,328.7 + ,292.9 + ,249.1 + ,230.4 + ,361.5 + ,321.7 + ,277.2 + ,260.7 + ,251 + ,257.6 + ,241.8 + ,287.5 + ,292.3 + ,274.7 + ,254.2 + ,230 + ,339 + ,318.2 + ,287 + ,295.8 + ,284 + ,271 + ,262.7 + ,340.6 + ,379.4 + ,373.3 + ,355.2 + ,338.4 + ,466.9 + ,451 + ,422 + ,429.2 + ,425.9 + ,460.7 + ,463.6 + ,541.4 + ,544.2 + ,517.5 + ,469.4 + ,439.4 + ,549 + ,533 + ,506.1 + ,484 + ,457 + ,481.5 + ,469.5 + ,544.7 + ,541.2 + ,521.5 + ,469.7 + ,434.4 + ,542.6 + ,517.3 + ,485.7 + ,465.8 + ,447 + ,426.6 + ,411.6 + ,467.5 + ,484.5 + ,451.2 + ,417.4 + ,379.9 + ,484.7 + ,455 + ,420.8 + ,416.5 + ,376.3 + ,405.6 + ,405.8 + ,500.8 + ,514 + ,475.5 + ,430.1 + ,414.4 + ,538 + ,526 + ,488.5 + ,520.2 + ,504.4 + ,568.5 + ,610.6 + ,818 + ,830.9 + ,835.9 + ,782 + ,762.3 + ,856.9 + ,820.9 + ,769.6 + ,752.2 + ,724.4 + ,723.1 + ,719.5 + ,817.4 + ,803.3 + ,752.5 + ,689 + ,630.4 + ,765.5 + ,757.7 + ,732.2 + ,702.6 + ,683.3 + ,709.5 + ,702.2 + ,784.8 + ,810.9 + ,755.6 + ,656.8 + ,615.1 + ,745.3 + ,694.1 + ,675.7 + ,643.7 + ,622.1 + ,634.6 + ,588 + ,689.7 + ,673.9 + ,647.9 + ,568.8 + ,545.7 + ,632.6 + ,643.8 + ,593.1 + ,579.7 + ,546 + ,562.9 + ,572.5) > par1 = '12' > par1 <- as.numeric(par1) > nx <- length(x) > x <- ts(x,frequency=par1) > m <- StructTS(x,type='BSM') > m$coef level slope seas epsilon 316.13794 23.67284 23.56443 0.00000 > m$fitted level slope sea Jan 1 235.1000 0.000000000 0.0000000 Feb 1 276.8962 3.229148950 3.8037913 Mar 1 265.9633 1.503089928 -1.3633330 Apr 1 241.8619 -2.617127605 -1.1618550 May 1 203.4005 -9.375644519 -2.0004654 Jun 1 231.5117 -1.642105312 9.2882530 Jul 1 239.5351 0.456224233 1.5649193 Aug 1 224.5051 -3.005394577 -0.7051136 Sep 1 205.6460 -6.609331477 0.4539944 Oct 1 175.3538 -12.045672404 -0.6538176 Nov 1 195.5606 -4.600414096 7.7394180 Dec 1 216.3860 1.288102911 4.1140381 Jan 2 288.8725 17.209580742 10.6274534 Feb 2 340.1774 24.913311380 7.2226190 Mar 2 345.1943 20.409084633 -6.8942720 Apr 2 331.3766 12.550409516 -3.6765980 May 2 356.2880 15.392470764 -4.6880282 Jun 2 388.4941 19.256292774 8.1059132 Jul 2 433.7705 25.235113635 5.0294671 Aug 2 408.5169 13.633798271 -12.9169352 Sep 2 368.9622 1.411559269 -5.4621834 Oct 2 379.1977 3.439497108 -0.3977115 Nov 2 357.7653 -2.276384942 -0.7652861 Dec 2 371.8553 1.474477906 -2.8552639 Jan 3 442.4615 17.234465143 22.3385466 Feb 3 468.2882 19.188649893 10.8117978 Mar 3 443.0351 9.140049766 -11.7350836 Apr 3 386.5649 -5.832636253 -20.0648570 May 3 341.6600 -14.772821901 -15.3600492 Jun 3 347.7917 -9.991556888 7.3083271 Jul 3 323.1287 -13.346243877 8.4712641 Aug 3 273.4883 -21.644959549 -12.1883448 Sep 3 254.6494 -21.003312350 -5.6493693 Oct 3 206.6888 -27.168134691 -1.1888131 Nov 3 227.5561 -16.189467704 8.0439075 Dec 3 250.4683 -7.275975145 -9.5683162 Jan 4 245.2838 -6.799051557 19.6161930 Feb 4 235.0728 -7.575690331 18.7272058 Mar 4 230.4435 -6.908955964 1.8565083 Apr 4 210.1414 -9.955394096 -16.3414041 May 4 197.8192 -10.495360002 -20.8192442 Jun 4 200.3571 -7.522003525 12.8429355 Jul 4 192.2756 -7.649593973 14.9243852 Aug 4 190.8668 -6.226329170 -10.2667711 Sep 4 187.5840 -5.554949344 1.0159838 Oct 4 185.6109 -4.738043880 -10.2108922 Nov 4 195.8239 -1.331219605 3.1761421 Dec 4 191.0662 -2.110652322 -11.4661923 Jan 5 202.3106 0.931776149 23.4894222 Feb 5 213.7964 3.332987347 20.2035804 Mar 5 199.7270 -0.608018535 0.4729821 Apr 5 199.0969 -0.613035196 -15.4969071 May 5 201.0347 -0.032190262 -22.8347350 Jun 5 192.2358 -2.028997921 10.9642038 Jul 5 193.6001 -1.256330319 14.8999006 Aug 5 200.6031 0.624223453 -8.8030625 Sep 5 178.1151 -4.638496711 -5.3150837 Oct 5 162.7386 -7.083082983 -14.7386379 Nov 5 155.1313 -7.202323755 4.2686984 Dec 5 164.7594 -3.377722328 -10.2593923 Jan 6 186.0398 2.234023286 27.1602439 Feb 6 175.9023 -0.578731220 20.4977273 Mar 6 181.0094 0.709477991 1.7906430 Apr 6 190.7086 2.748954572 -14.3086327 May 6 178.7527 -0.594841765 -25.1526604 Jun 6 166.0707 -3.344748596 7.1292505 Jul 6 158.4006 -4.328592304 12.5994397 Aug 6 154.4402 -4.244850299 -3.2401785 Sep 6 161.6550 -1.638630774 0.2450452 Oct 6 169.7023 0.563582541 -12.5023496 Nov 6 195.7487 6.352699420 5.9513448 Dec 6 242.9256 15.623879681 -6.5256470 Jan 7 314.5870 28.366018479 41.5130330 Feb 7 374.3714 35.504516063 23.9285794 Mar 7 406.4237 34.722202785 -2.7236804 Apr 7 404.9300 26.510672167 -20.3300457 May 7 396.0169 18.463719087 -30.2168992 Jun 7 369.1593 8.161960649 -1.0593312 Jul 7 357.5609 3.671020455 10.3391203 Aug 7 352.2865 1.638328789 -5.2865341 Sep 7 344.9887 -0.392057168 -1.6887485 Oct 7 315.8812 -6.914291565 -22.9811775 Nov 7 312.5406 -6.103083575 -1.0406350 Dec 7 317.6009 -3.569116929 -16.7008629 Jan 8 329.8230 0.019001373 37.0770137 Feb 8 332.8217 0.695615450 24.0783198 Mar 8 327.1200 -0.754106272 2.5799831 Apr 8 328.6220 -0.242749694 -12.4220321 May 8 297.2709 -7.303937503 -28.2708508 Jun 8 286.4950 -8.092545590 2.8049902 Jul 8 258.5257 -12.606984862 7.6742653 Aug 8 253.7614 -10.826083270 -0.1614137 Sep 8 231.6569 -13.386717831 2.1431039 Oct 8 245.3460 -7.241715874 -16.9460253 Nov 8 254.2649 -3.575647919 -0.6649007 Dec 8 275.2111 1.988301347 -15.1111016 Jan 9 272.3602 0.889409797 34.2397556 Feb 9 282.3331 2.950986222 26.8669024 Mar 9 303.5743 7.095513597 5.9257333 Apr 9 283.8362 1.015367294 -12.8362244 May 9 302.3120 4.976220895 -22.4119821 Jun 9 310.4355 5.690661378 7.4645017 Jul 9 296.2011 1.167716511 2.1988546 Aug 9 253.7589 -8.729585380 -7.0588587 Sep 9 232.3520 -11.605991284 -5.0520340 Oct 9 227.5112 -10.071558964 -18.4112330 Nov 9 256.3571 -1.247266870 3.5428641 Dec 9 276.1129 3.516516273 -10.1129313 Jan 10 287.5232 5.308111520 33.0767894 Feb 10 286.9885 3.982610157 21.5115414 Mar 10 275.0993 0.386566128 7.1007349 Apr 10 279.1338 1.212938704 -16.4337583 May 10 285.7946 2.448178169 -22.2946206 Jun 10 298.3055 4.731221849 14.7945371 Jul 10 277.9384 -0.963365036 6.3616048 Aug 10 259.6329 -4.897281759 -7.0328531 Sep 10 256.2963 -4.543350856 -5.9962816 Oct 10 269.4954 -0.521188830 -22.9954066 Nov 10 305.7990 7.825305600 6.9010173 Dec 10 339.8164 13.764003955 -6.6163832 Jan 11 401.3663 24.604637511 45.0336882 Feb 11 476.6716 36.101910133 34.9283687 Mar 11 511.6172 35.839953296 3.8828465 Apr 11 529.2442 31.715052762 -22.8442102 May 11 517.2953 21.818939898 -34.0952989 Jun 11 507.6079 14.673942745 14.6921490 Jul 11 502.4117 10.167462236 7.3883272 Aug 11 474.9233 1.629145825 -14.2232785 Sep 11 425.3098 -9.986229604 -19.5097685 Oct 11 405.6629 -12.175341000 -30.6628701 Nov 11 380.1126 -15.205813512 -1.6125747 Dec 11 413.2667 -4.244341621 -6.4667078 Jan 12 430.8166 0.697828737 36.9833914 Feb 12 435.2706 1.549292969 34.5294264 Mar 12 425.3630 -1.045570601 4.4370491 Apr 12 380.0533 -11.068568065 -24.2533078 May 12 361.5516 -12.752635297 -28.8516420 Jun 12 356.9980 -10.894010346 21.0019710 Jul 12 344.4986 -11.257979414 16.0014061 Aug 12 336.3657 -10.549646037 -1.6656740 Sep 12 334.1861 -8.653098725 -14.6860907 Oct 12 346.9750 -3.796066531 -23.8750155 Nov 12 370.6208 2.419830035 -7.0207914 Dec 12 366.1868 0.866774879 -14.0868108 Jan 13 374.1234 2.469359279 37.7766483 Feb 13 355.7341 -2.257465571 32.8659033 Mar 13 392.5778 6.596852815 23.8221958 Apr 13 387.1184 3.867388979 -26.4183694 May 13 372.2095 -0.385346791 -34.2094577 Jun 13 390.6387 3.878198101 26.5613001 Jul 13 377.2612 -0.032562593 11.1388358 Aug 13 374.7859 -0.586045386 -3.6859178 Sep 13 355.5203 -4.817201952 -24.0202605 Oct 13 376.7754 1.086891094 -23.0754152 Nov 13 398.2560 5.705092488 -1.5559694 Dec 13 451.5173 16.478269722 -4.5173420 Jan 14 488.6197 21.151824398 44.8802682 Feb 14 535.5992 27.002982431 29.8007556 Mar 14 525.0068 18.491215667 17.2931809 Apr 14 516.8796 12.466058256 -28.1796411 May 14 509.1277 7.888003637 -42.0277436 Jun 14 503.2876 4.778065455 28.0124011 Jul 14 487.5935 0.139757067 8.5065431 Aug 14 451.1066 -8.156961602 -7.1065873 Sep 14 433.8331 -10.221365706 -30.4331263 Oct 14 415.9835 -11.948337177 -29.6834943 Nov 14 405.9277 -11.519874586 -11.8276575 Dec 14 410.5976 -7.853234964 -6.4975982 Jan 15 419.3384 -4.094045531 42.7616002 Feb 15 411.5593 -4.928667687 36.5407468 Mar 15 408.9603 -4.401312299 23.3397365 Apr 15 409.5354 -3.275066264 -23.2353894 May 15 429.2301 1.924890335 -34.0301068 Jun 15 397.2618 -5.751047697 24.6382305 Jul 15 370.1632 -10.586326008 12.7367714 Aug 15 382.9972 -5.282509192 1.2027542 Sep 15 375.1694 -5.858739606 -29.6694415 Oct 15 356.4138 -8.777828264 -33.0137783 Nov 15 380.2985 -1.384551328 -7.6985045 Dec 15 385.3257 0.067237597 -9.3257196 Jan 16 412.9703 6.312890979 49.7296863 Feb 16 445.8812 12.335501160 41.1187904 Mar 16 429.9336 5.934299493 14.2664012 Apr 16 427.9874 4.151099527 -28.6874312 May 16 422.9717 2.076321047 -28.0717220 Jun 16 426.0115 2.294455411 29.3885416 Jul 16 410.1490 -1.817112278 3.8509883 Aug 16 379.1318 -8.428264664 -3.6318005 Sep 16 372.8591 -7.940371322 -25.8591041 Oct 16 376.7006 -5.274191201 -37.3005855 Nov 16 391.2115 -0.796609443 -5.4114575 Dec 16 394.5173 0.132089509 -15.7172760 Jan 17 405.1946 2.519771628 46.6053924 Feb 17 400.8264 0.960457713 45.2736118 Mar 17 405.6192 1.827684981 16.8807891 Apr 17 409.7536 2.349568887 -26.6535742 May 17 386.7231 -3.393802745 -33.9230916 Jun 17 405.4153 1.605755441 39.8846984 Jul 17 366.8695 -7.484363100 0.6304831 Aug 17 358.3531 -7.717990183 -3.2530528 Sep 17 354.1341 -6.926173159 -27.9340704 Oct 17 358.8518 -4.291651199 -39.0518455 Nov 17 341.6405 -7.215035754 -9.8405015 Dec 17 354.0064 -2.783205214 -13.1063623 Jan 18 347.6375 -3.594900992 46.4624940 Feb 18 367.5637 1.728790605 49.6363124 Mar 18 356.6930 -1.121932278 13.2069822 Apr 18 367.8822 1.663076536 -18.6821523 May 18 361.4648 -0.165189131 -40.0647860 Jun 18 357.5812 -1.006742397 48.1187767 Jul 18 344.6390 -3.708331832 -1.7389802 Aug 18 324.1549 -7.504977531 -7.6549204 Sep 18 314.2769 -8.041899573 -30.0769065 Oct 18 307.1386 -7.837482614 -36.2386156 Nov 18 302.0906 -7.206392129 -13.2906086 Dec 18 292.3449 -7.781035741 -13.5448610 Jan 19 283.1557 -8.099730208 41.2442773 Feb 19 261.9897 -11.056595614 48.9103126 Mar 19 281.2960 -4.187679326 17.7040360 Apr 19 288.3374 -1.647728893 -15.3373923 May 19 312.7058 4.237776622 -33.4057552 Jun 19 310.2937 2.733036979 48.9062760 Jul 19 304.6813 0.844402323 0.3186732 Aug 19 292.0696 -2.200447868 -9.9695765 Sep 19 282.0055 -3.979416202 -31.7054518 Oct 19 282.0158 -3.076964341 -35.5157742 Nov 19 272.0180 -4.642529342 -14.1179532 Dec 19 276.7470 -2.522125688 -10.2469764 Jan 20 272.8482 -2.833657244 43.0518450 Feb 20 275.1345 -1.675195326 43.2654789 Mar 20 279.6384 -0.277493280 15.7616243 Apr 20 286.0971 1.246037748 -19.6971194 May 20 279.6647 -0.490795393 -33.8647377 Jun 20 305.5490 5.476495053 57.2510366 Jul 20 320.0383 7.515824390 4.8617395 Aug 20 307.2777 2.928399683 -13.0777351 Sep 20 319.1848 4.959343054 -29.6848022 Oct 20 328.5354 5.952490041 -33.3353522 Nov 20 311.6184 0.779817532 -21.3184147 Dec 20 287.1272 -4.937193735 -15.1271853 Jan 21 268.1136 -8.122039873 39.2864385 Feb 21 281.5680 -3.240818177 47.1320048 Mar 21 278.8033 -3.133120422 14.0966539 Apr 21 269.2264 -4.590371662 -20.1264267 May 21 269.1765 -3.563463570 -38.7764595 Jun 21 298.5063 3.877538429 62.9937057 Jul 21 311.5983 5.962182840 10.1017381 Aug 21 297.4296 1.408288386 -20.2295737 Sep 21 292.0210 -0.133477506 -31.3210328 Oct 21 281.0751 -2.578650905 -30.0751092 Nov 21 273.7604 -3.649762985 -16.1603552 Dec 21 257.1145 -6.589467979 -15.3145006 Jan 22 252.1209 -6.228438747 35.3790614 Feb 22 245.1816 -6.389246074 47.1184074 Mar 22 255.3919 -2.635211379 19.3081304 Apr 22 272.1772 1.756331646 -17.9772271 May 22 276.3242 2.296965797 -46.3241763 Jun 22 277.9307 2.140786289 61.0693420 Jul 22 299.2417 6.477241168 18.9582763 Aug 22 305.9597 6.531687145 -18.9596769 Sep 22 322.3049 8.750986192 -26.5048620 Oct 22 316.1983 5.391328305 -32.1982724 Nov 22 290.7627 -1.579800129 -19.7626810 Dec 22 279.5216 -3.764930117 -16.8215868 Jan 23 299.5949 1.627125386 41.0051398 Feb 23 330.2320 8.188459763 49.1679611 Mar 23 355.0736 11.954279315 18.2263967 Apr 23 372.6773 13.231686164 -17.4773485 May 23 385.2830 13.090117413 -46.8829793 Jun 23 407.8946 15.243531192 59.0054185 Jul 23 430.8821 16.995062096 20.1179402 Aug 23 443.7949 16.071819893 -21.7949218 Sep 23 452.8655 14.488648806 -23.6655059 Oct 23 453.6079 11.380523331 -27.7078677 Nov 23 475.6861 13.799466416 -14.9860547 Dec 23 486.9357 13.222823331 -23.3357053 Jan 24 505.6608 14.467264348 35.7392030 Feb 24 502.8377 10.557020322 41.3622999 Mar 24 502.5008 8.093749034 14.9991521 Apr 24 491.2081 3.710558306 -21.8081472 May 24 489.4681 2.478118511 -50.0680925 Jun 24 491.7209 2.427176830 57.2790535 Jul 24 508.6558 5.708186527 24.3442135 Aug 24 524.2704 7.948443566 -18.1704211 Sep 24 510.3236 2.997723738 -26.3236365 Oct 24 491.6310 -1.906266072 -34.6310226 Nov 24 494.7166 -0.777596256 -13.2166159 Dec 24 494.0574 -0.750819722 -24.5574315 Jan 25 502.9014 1.419007787 41.7985958 Feb 25 498.6112 0.127977852 42.5887914 Mar 25 501.3719 0.723222088 20.1281468 Apr 25 492.6025 -1.422881444 -22.9024771 May 25 485.8885 -2.619166015 -51.4885137 Jun 25 487.7976 -1.595220396 54.8023688 Jul 25 493.2491 -0.001713744 24.0509155 Aug 25 497.7211 1.009897284 -12.0211082 Sep 25 489.6468 -1.043989643 -23.8467802 Oct 25 483.6264 -2.169043735 -36.6263770 Nov 25 447.7428 -9.791471690 -21.1427942 Dec 25 437.4801 -9.898022419 -25.8800939 Jan 26 425.2195 -10.432255765 42.2804701 Feb 26 437.1644 -5.372494446 47.3356228 Mar 26 429.9211 -5.795457501 21.2789304 Apr 26 436.4255 -3.014836111 -19.0254633 May 26 433.0837 -3.088753894 -53.1836738 Jun 26 431.3934 -2.772548747 53.3065922 Jul 26 431.3197 -2.162301469 23.6803333 Aug 26 430.5506 -1.847273128 -9.7506479 Sep 26 436.5997 -0.062062389 -20.0997457 Oct 26 411.3169 -5.763601313 -35.0169148 Nov 26 421.9700 -2.052219843 -16.3699688 Dec 26 429.7659 0.174416058 -23.9659092 Jan 27 457.2404 6.347212982 43.5595742 Feb 27 466.4735 6.999687992 47.5265466 Mar 27 459.9322 3.938461951 15.5677621 Apr 27 451.4793 1.137278842 -21.3792988 May 27 464.7966 3.890797209 -50.3966123 Jun 27 482.4301 6.997883702 55.5698816 Jul 27 500.4672 9.493854796 25.5328037 Aug 27 501.3437 7.545559166 -12.8437075 Sep 27 529.8578 12.285863163 -9.6577870 Oct 27 543.3368 12.555581895 -38.9368075 Nov 27 581.6843 18.386178075 -13.1843475 Dec 27 633.5116 25.946619770 -22.9116025 Jan 28 753.7163 47.257742333 64.2837150 Feb 28 785.5376 43.767822020 45.3624175 Mar 28 819.1353 41.468746283 16.7647383 Apr 28 815.8550 31.353287836 -33.8550399 May 28 820.4617 25.307026591 -58.1617390 Jun 28 810.4888 17.331069889 46.4111572 Jul 28 799.1554 10.850416750 21.7446100 Aug 28 790.3670 6.410532387 -20.7669662 Sep 28 768.3964 -0.005207084 -16.1964082 Oct 28 769.0020 0.132854184 -44.6019693 Nov 28 750.7352 -4.026424060 -27.6351976 Dec 28 760.0623 -1.007590658 -40.5623101 Jan 29 752.3667 -2.519622746 65.0333331 Feb 29 754.3096 -1.510771812 48.9904081 Mar 29 731.1354 -6.407812888 21.3645795 Apr 29 717.8011 -7.973492327 -28.8010618 May 29 685.9672 -13.367080390 -55.5671675 Jun 29 704.7419 -6.100950549 60.7580675 Jul 29 725.8339 0.046630963 31.8661442 Aug 29 743.4857 4.026559534 -11.2857344 Sep 29 724.2519 -1.231387156 -21.6519115 Oct 29 723.5116 -1.120379310 -40.2116290 Nov 29 736.7509 2.125512361 -27.2508515 Dec 29 741.2668 2.665902810 -39.0668493 Jan 30 724.5982 -1.705004525 60.2017808 Feb 30 750.0377 4.431270311 60.8622763 Mar 30 736.6108 0.394564141 18.9891738 Apr 30 690.9366 -10.018493300 -34.1366176 May 30 677.8872 -10.703600601 -62.7872014 Jun 30 686.5981 -6.314874199 58.7018953 Jul 30 668.7639 -8.918953013 25.3360918 Aug 30 677.5986 -4.905660609 -1.8986074 Sep 30 667.5983 -6.057246776 -23.8983096 Oct 30 664.7912 -5.322615825 -42.6912136 Nov 30 661.7012 -4.817978642 -27.1011567 Dec 30 629.9775 -10.899991314 -41.9774619 Jan 31 631.6506 -8.057752495 58.0494011 Feb 31 611.2299 -10.852403777 62.6701475 Mar 31 615.0099 -7.544949813 32.8900518 Apr 31 603.9108 -8.348300596 -35.1107611 May 31 609.2113 -5.263239118 -63.5112612 Jun 31 578.1020 -11.105593632 54.4979850 Jul 31 611.4408 -1.058872986 32.3592280 Aug 31 598.0401 -3.848678431 -4.9400981 Sep 31 602.1679 -2.045748153 -22.4678760 Oct 31 590.8201 -4.148228266 -44.8200832 Nov 31 584.5428 -4.629447480 -21.6428330 Dec 31 609.9050 2.149881461 -37.4050482 > m$resid Jan Feb Mar Apr May 1 0.000000000 1.420674755 -0.734902934 -1.293650448 -1.772732613 2 3.832200517 1.443034792 -0.929075082 -1.618598848 0.582408732 3 3.411721293 0.388212764 -2.058852572 -3.090383039 -1.833789539 4 0.100342756 -0.157152943 0.136376511 -0.628825595 -0.110924973 5 0.632935552 0.489352920 -0.806261386 -0.001034630 0.119450189 6 1.161389426 -0.575048317 0.263722966 0.420233743 -0.688063004 7 2.630025121 1.461783767 -0.160265645 -1.690731765 -1.656298043 8 0.739491749 0.138682043 -0.297163294 0.105230082 -1.453505466 9 -0.226272568 0.422797886 0.849933422 -1.250736633 0.815289958 10 0.368698803 -0.271948693 -0.737719924 0.169947331 0.254234999 11 2.230107967 2.359541063 -0.053755143 -0.848152074 -2.036572067 12 1.016437114 0.174781352 -0.532603410 -2.060647255 -0.346531687 13 0.329540457 -0.970452284 1.817712592 -0.561106760 -0.874986770 14 0.960909086 1.201457658 -1.747658112 -1.238539496 -0.941817114 15 0.772843064 -0.171398982 0.108291922 0.231502543 1.069649641 16 1.283948095 1.236935182 -1.314624273 -0.366529512 -0.426750150 17 0.490824069 -0.320282672 0.178120444 0.107268697 -1.181225457 18 -0.166850517 1.093567239 -0.585559520 0.572424966 -0.375986905 19 -0.065508466 -0.607425109 1.411025643 0.522049947 1.210286148 20 -0.064034834 0.237995112 0.287136290 0.313136961 -0.357138217 21 -0.654630153 1.002852152 0.022126039 -0.299512320 0.211147784 22 0.074206967 -0.033039519 0.771287015 0.902600087 0.111157219 23 1.108287713 1.348147163 0.773740844 0.262546351 -0.029106040 24 0.255781510 -0.803459971 -0.506132714 -0.900878114 -0.253375723 25 0.445981994 -0.265283470 0.122309908 -0.441088321 -0.245934354 26 -0.109804684 1.039718679 -0.086912352 0.571499947 -0.015195699 27 1.268732287 0.134078844 -0.629050688 -0.575725475 0.566041490 28 4.380187970 -0.717168522 -0.472447339 -2.079022818 -1.242902450 29 -0.310775003 0.207319885 -1.006335103 -0.321792832 -1.108712469 30 -0.898370551 1.261031822 -0.829552259 -2.140186806 -0.140828910 31 0.584175668 -0.574321796 0.679699987 -0.165111983 0.634147144 Jun Jul Aug Sep Oct 1 1.830199805 0.467982211 -0.745971220 -0.761334481 -1.135254174 2 0.792932807 1.228119574 -2.383783834 -2.511697815 0.416793837 3 0.980733924 -0.688869355 -1.705030328 0.131862609 -1.267029179 4 0.609997605 -0.026196531 0.292408231 0.137973631 0.167878010 5 -0.409824893 0.158635895 0.386331402 -1.081451753 -0.502314238 6 -0.564670401 -0.202002782 0.017202146 0.535498527 0.452480711 7 -2.116356061 -0.922183167 -0.417520206 -0.417131966 -1.340085064 8 -0.162070030 -0.927139145 0.365779505 -0.526013998 1.262610927 9 0.146869231 -0.929021252 -2.032726264 -0.590835230 0.315293043 10 0.469423751 -1.169837111 -0.807940616 0.072696523 0.826507896 11 -1.469292832 -0.925873780 -1.753587139 -2.385715126 -0.449857067 12 0.382234467 -0.074786145 0.145479131 0.389536733 0.998145814 13 0.876845703 -0.803622032 -0.113679016 -0.869061102 1.213358985 14 -0.639596167 -0.953183748 -1.704116978 -0.424030899 -0.354920773 15 -1.578624153 -0.993707533 1.089433355 -0.118362453 -0.599930808 16 0.044859968 -0.845005478 -1.358030600 0.100221230 0.547960144 17 1.028136235 -1.868239542 -0.047992798 0.162658870 0.541458724 18 -0.173054536 -0.555252054 -0.779961350 -0.110301769 0.042012965 19 -0.309417141 -0.388172012 -0.625544578 -0.365474840 0.185478028 20 1.226992397 0.419147902 -0.942496013 0.417257749 0.204118962 21 1.529954013 0.428463936 -0.935643752 -0.316768087 -0.502551348 22 -0.032111025 0.891288950 0.011186881 0.455988743 -0.690504463 23 0.442732962 0.359999763 -0.189702558 -0.325297176 -0.638808115 24 -0.010473048 0.674360562 0.460329059 -1.017264210 -1.007909990 25 0.210505456 0.327520463 0.207871925 -0.422040145 -0.231230870 26 0.065004475 0.125426729 0.064735494 0.366840630 -1.171830142 27 0.638729050 0.513007060 -0.400365965 0.974100558 0.055434969 28 -1.639593584 -1.331993269 -0.912393950 -1.318417616 0.028375575 29 1.493646025 1.263534103 0.817887431 -1.080513586 0.022815321 30 0.902142382 -0.535224768 0.824756489 -0.236655957 0.150987924 31 -1.200929148 2.064932298 -0.573330151 0.370515286 -0.432120608 Nov Dec 1 1.544403291 1.216753779 2 -1.174731806 0.771881400 3 2.255851604 1.838219751 4 0.700076701 -0.160873910 5 -0.024510022 0.789316568 6 1.190313836 1.912510418 7 0.166832923 0.522447989 8 0.754074494 1.146610252 9 1.815211570 0.981308329 10 1.716969655 1.222914430 11 -0.623396890 2.256583277 12 1.278627108 -0.319645549 13 0.949932644 2.216879931 14 0.088127072 0.754391767 15 1.520576946 0.298657560 16 0.920851700 0.191027164 17 -0.601184005 0.911508269 18 0.129774534 -0.118178703 19 -0.321919079 0.436040902 20 -1.063579422 -1.175573752 21 -0.220227132 -0.604449760 22 -1.433248808 -0.449275093 23 0.497311324 -0.118555944 24 0.232035975 0.005504958 25 -1.566999590 -0.021904909 26 0.762956223 0.457742584 27 1.198579043 1.554203440 28 -0.854992880 0.620568546 29 0.667222012 0.111083451 30 0.103730943 -1.250204754 31 -0.098915784 1.393521180 > mylevel <- as.numeric(m$fitted[,'level']) > myslope <- as.numeric(m$fitted[,'slope']) > myseas <- as.numeric(m$fitted[,'sea']) > myresid <- as.numeric(m$resid) > myfit <- mylevel+myseas > postscript(file="/var/wessaorg/rcomp/tmp/1lld81352555950.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time') > grid() > dev.off() null device 1 > mylagmax <- nx/2 > postscript(file="/var/wessaorg/rcomp/tmp/2bga91352555950.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/wessaorg/rcomp/tmp/3ruso1352555950.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/wessaorg/rcomp/tmp/4x3ol1352555950.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/wessaorg/rcomp/tmp/55fz31352555950.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/6b4my1352555950.tab") > > try(system("convert tmp/1lld81352555950.ps tmp/1lld81352555950.png",intern=TRUE)) character(0) > try(system("convert tmp/2bga91352555950.ps tmp/2bga91352555950.png",intern=TRUE)) character(0) > try(system("convert tmp/3ruso1352555950.ps tmp/3ruso1352555950.png",intern=TRUE)) character(0) > try(system("convert tmp/4x3ol1352555950.ps tmp/4x3ol1352555950.png",intern=TRUE)) character(0) > try(system("convert tmp/55fz31352555950.ps tmp/55fz31352555950.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 9.783 0.711 10.674