R version 2.13.0 (2011-04-13) Copyright (C) 2011 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(-45.6 + ,16.1 + ,23.9 + ,39.3 + ,-39.4 + ,-0.3 + ,17.3 + ,17.7 + ,31.4 + ,-28.6 + ,-17.2 + ,-79 + ,-47.9 + ,9.1 + ,10.6 + ,-23.9 + ,-45 + ,-42.2 + ,43.2 + ,32.1 + ,-15.3 + ,21.8 + ,-12 + ,-95.8 + ,-14.3 + ,47.8 + ,64.8 + ,40.2 + ,-28.8 + ,23.5 + ,70.3 + ,12.3 + ,43.5 + ,-30.1 + ,-5.3 + ,-24 + ,11.1 + ,21.5 + ,38.5 + ,16.8 + ,-36.2 + ,6 + ,26.6 + ,-8 + ,13.2 + ,-23.6 + ,19.4 + ,-46.2 + ,-8.2 + ,33.8 + ,16.6 + ,5.4 + ,-25 + ,-5.3 + ,16.7 + ,19 + ,24.8 + ,-11.4 + ,4.9 + ,-58.7 + ,16.8 + ,13.6 + ,6.4 + ,22.8 + ,-19.6 + ,2.2 + ,19.8 + ,-10.7 + ,4.7 + ,-44.5 + ,-34.7 + ,-119.7 + ,-42.2 + ,-5.4 + ,19.1 + ,18.8 + ,-2.3 + ,0.2 + ,20.9 + ,3.7 + ,50.4 + ,-18.6 + ,10.6 + ,-66 + ,10 + ,27.2 + ,13.5 + ,47.2 + ,-20.3 + ,23.1 + ,12.6 + ,19.8 + ,5.4 + ,-25.2 + ,-6.5 + ,-46.5 + ,-2.6 + ,-0.3 + ,38.5 + ,-8.9 + ,-38 + ,19.5 + ,51.7 + ,19.4 + ,18.2 + ,-50.8 + ,-6.1 + ,-54.6 + ,12.1 + ,26.3 + ,19.5 + ,-0.8 + ,-49.6 + ,28.8 + ,31.7 + ,2.3 + ,3.8 + ,-66.2 + ,-20.5 + ,-113.2 + ,-65.2 + ,-3.9 + ,9.1 + ,23.2 + ,-39.1 + ,12.5 + ,49.1 + ,54.9 + ,30.8 + ,-3.5 + ,-28.3 + ,-61 + ,-2 + ,40 + ,74 + ,23.1 + ,-45.3 + ,17.5 + ,25.8 + ,15.2 + ,-3.6 + ,-40.5 + ,11.5 + ,-59.8 + ,23.3 + ,-27.8 + ,55.7 + ,22.7 + ,-79.2 + ,28.8 + ,17.3 + ,39.6 + ,-22.2 + ,-43 + ,-50.3 + ,-86.5 + ,-31.9 + ,23.1 + ,53.6 + ,21.6 + ,-64.2 + ,35.2 + ,52.1 + ,40.6 + ,17.1 + ,-7.8 + ,-10 + ,-58 + ,14 + ,15.8 + ,46 + ,-8.9 + ,-26.7 + ,39 + ,-1.3 + ,38.7 + ,22.1 + ,-49.2 + ,-3.4 + ,-86.7 + ,-24.3 + ,42.8 + ,44.9 + ,4.4 + ,-60.5 + ,41.4 + ,38.5 + ,28.5 + ,7.6 + ,-46.4 + ,7 + ,-73 + ,5.7 + ,23.6 + ,39.4 + ,30.3 + ,-92.5 + ,77.8 + ,12.4 + ,28.9 + ,6.4 + ,-12 + ,-9.1 + ,-53.2 + ,-23.1 + ,47.3 + ,20.7 + ,27.8 + ,-84.3 + ,62.8 + ,26.4 + ,32.3 + ,13.3 + ,-17.9 + ,10 + ,-45.6 + ,13.5 + ,11.9 + ,26 + ,-6.3 + ,-79.9 + ,54.2 + ,22.9 + ,31.8 + ,3.8 + ,-11.4 + ,-8.6 + ,-49.4 + ,-2.5 + ,23 + ,29 + ,20.6 + ,-117 + ,37.9 + ,30.7 + ,4.7 + ,-5.7 + ,4.9 + ,18.3 + ,-35.4 + ,-21.3 + ,35.8 + ,43.8 + ,18.7 + ,-131.1 + ,39.8 + ,44.5 + ,16.5 + ,9.7 + ,-6.6 + ,15.8 + ,-45.7 + ,-4.8 + ,17.6 + ,20.5 + ,24.2 + ,-109 + ,20.8 + ,31.2 + ,-8.8 + ,11.8 + ,13 + ,8.3 + ,-77.9 + ,-38.8 + ,6.1 + ,18.1 + ,16.8 + ,-128.5 + ,15.9 + ,29 + ,-7.2 + ,3.3 + ,-34.8 + ,-2.9 + ,-77.8 + ,-2.8 + ,26.7 + ,48.1 + ,30 + ,-109.6 + ,16 + ,26.9 + ,22.1 + ,27 + ,-24.5 + ,12 + ,-75.2 + ,3.5 + ,19.7 + ,51.8 + ,35.3 + ,-108.2 + ,25.3 + ,31.6 + ,19.9 + ,18.8 + ,20.4 + ,15 + ,-55.9 + ,-17 + ,33.3 + ,33.8 + ,37.5 + ,-104.8 + ,29.7 + ,34.2 + ,4.3 + ,40.2 + ,-29.3 + ,-0.2 + ,-95 + ,-13.2 + ,38.5 + ,45.4 + ,15.7 + ,-123.6 + ,12 + ,37.5 + ,-31.7 + ,15.8 + ,-64.1 + ,-42.1 + ,-207.4 + ,-12.9 + ,-5 + ,53.9 + ,19.7 + ,-94.6 + ,36 + ,51.3 + ,17.4 + ,27.8 + ,1.3 + ,3.6 + ,-97.9 + ,14.1 + ,50.8 + ,63.5 + ,58.6 + ,-135.1 + ,7.8 + ,25.5 + ,29.6 + ,19.3 + ,-26.2 + ,7.3 + ,-82.6 + ,-26.1 + ,55.3 + ,98.8 + ,41.7 + ,-130.2 + ,51.2 + ,18.4 + ,32 + ,21.6 + ,-12.5 + ,46.6 + ,-101.7 + ,15.8 + ,26 + ,79.1 + ,23.1 + ,-86.9 + ,-11.2 + ,50.7 + ,13.4 + ,33.7 + ,-16.9 + ,-9.6) > par1 = '12' > par1 <- as.numeric(par1) > nx <- length(x) > x <- ts(x,frequency=par1) > m <- StructTS(x,type='BSM') > m$coef level slope seas epsilon 43.24048 0.00000 51.34478 239.83846 > m$fitted level slope sea Jan 1 -45.6000000 0.0000000 0.00000000 Feb 1 -26.3080994 1.9747310 12.07581796 Mar 1 -5.4891288 3.8789477 7.85622494 Apr 1 12.6348315 5.0403345 9.19154468 May 1 -1.5301573 3.7670203 -12.50612153 Jun 1 -1.5242857 3.5568970 6.44094499 Jul 1 5.3710653 3.7197619 7.14993876 Aug 1 10.9332464 3.8005897 4.07410099 Sep 1 18.8909601 3.9683079 6.34817408 Oct 1 6.2127422 3.3404952 -9.90290295 Nov 1 -1.3051982 2.9531819 0.46680940 Dec 1 -24.9766820 2.0475558 -13.69713590 Jan 2 -24.4712643 2.1723069 -20.48659472 Feb 2 -14.6161046 2.3612517 13.45325976 Mar 2 -4.7926657 2.6632599 6.36269052 Apr 2 -11.9835600 2.2818950 0.54838190 May 2 -17.4214087 2.0206080 -17.30131674 Jun 2 -25.1067756 1.7342863 -3.72146251 Jul 2 -6.8394199 2.1686595 26.78258873 Aug 2 7.3968444 2.4583218 7.51212439 Sep 2 1.1954036 2.2643242 -4.06148301 Oct 2 9.1607266 2.3849512 4.41011390 Nov 2 2.8423042 2.2146023 -2.21643551 Dec 2 -20.4436657 1.8556457 -37.88940997 Jan 3 -14.7960755 1.7794367 -5.56962117 Feb 3 0.9548755 1.9428596 27.17714818 Mar 3 19.4146516 2.3478359 23.80609549 Apr 3 27.9129446 2.5099289 4.22388337 May 3 18.7427635 2.2235973 -31.84527834 Jun 3 23.9004606 2.2881123 -4.43226971 Jul 3 32.6633455 2.4161854 28.60085348 Aug 3 26.5635714 2.2621692 -2.25916008 Sep 3 33.2455164 2.3363313 3.98302089 Oct 3 14.9931561 2.0168103 -15.73511123 Nov 3 5.6035601 1.8632444 5.45082232 Dec 3 8.6178868 1.8727956 -34.28770328 Jan 4 14.7544516 1.8531372 -10.06663769 Feb 4 13.4522336 1.8269669 12.52985068 Mar 4 15.2267996 1.8260773 23.34415285 Apr 4 14.4539935 1.7750684 5.83828684 May 4 10.9848905 1.6740510 -40.05585921 Jun 4 12.1726514 1.6653703 -5.50190382 Jul 4 8.3372101 1.5756803 25.94064517 Aug 4 4.8337969 1.4998530 -5.68381181 Sep 4 3.2421798 1.4575126 14.33623439 Oct 4 -0.5736105 1.3924815 -15.52184294 Nov 4 3.9495127 1.4245732 10.97197807 Dec 4 1.4274580 1.3990388 -41.93300067 Jan 5 1.2751649 1.3973252 -7.20309999 Feb 5 7.0791666 1.4290398 20.45191413 Mar 5 4.1905669 1.3733976 18.36833795 Apr 5 2.6193507 1.3280646 6.80657870 May 5 6.2731031 1.3646024 -34.46828019 Jun 5 4.8526925 1.3228727 -6.29031357 Jul 5 0.8340653 1.2486014 23.34090284 Aug 5 6.9045341 1.3101790 5.29887605 Sep 5 8.6902554 1.3157017 15.43575132 Oct 5 8.8019180 1.3033302 -18.48774428 Nov 5 5.0826216 1.2609069 7.00013497 Dec 5 -0.5697972 1.2203616 -48.18616414 Jan 6 6.2186044 1.2398051 2.52657728 Feb 6 3.3969796 1.2125345 15.98215334 Mar 6 -0.7639573 1.1563095 14.66228146 Apr 6 4.1069421 1.2029646 13.55297906 May 6 7.7423478 1.2349234 -30.71344239 Jun 6 8.6343433 1.2305294 -5.95619870 Jul 6 6.9148758 1.1949539 17.02638789 Aug 6 1.2465968 1.1185763 -2.25412502 Sep 6 -2.4285829 1.0702243 13.93133126 Oct 6 -9.5306589 0.9977265 -23.32574759 Nov 6 -19.2612377 0.9186818 -0.09697961 Dec 6 -33.4432812 0.8337045 -64.58081812 Jan 7 -38.7236493 0.8060272 5.31500233 Feb 7 -35.1626339 0.8236503 25.84151758 Mar 7 -23.1829270 0.9230594 26.60816044 Apr 7 -13.3121003 1.0176817 19.62529733 May 7 -0.4675566 1.1502597 -18.33720181 Jun 7 2.8060795 1.1738470 -5.58086832 Jul 7 2.9601009 1.1630570 19.37595185 Aug 7 3.2211106 1.1541964 1.75529580 Sep 7 10.8828063 1.2122248 30.27075175 Oct 7 8.6191939 1.1848825 -22.26335804 Nov 7 7.4858889 1.1694235 6.42919071 Dec 7 5.3496639 1.1512947 -66.61109535 Jan 8 6.8770835 1.1531574 2.58371782 Feb 8 8.5342830 1.1562424 17.94799847 Mar 8 5.4731683 1.1231688 13.97972260 Apr 8 13.4760816 1.1859965 24.06419907 May 8 11.2172873 1.1524828 -26.68359216 Jun 8 16.3015758 1.1907983 1.26750532 Jul 8 11.5275594 1.1348916 9.49530203 Aug 8 14.1197477 1.1476595 3.61432720 Sep 8 4.0700858 1.0581424 17.25911108 Oct 8 1.2153808 1.0303111 -20.83276051 Nov 8 -2.8123111 0.9990950 3.54578959 Dec 8 3.3386364 1.0266611 -57.21764637 Jan 9 2.2919780 1.0161217 -1.92403226 Feb 9 -3.0177400 0.9790835 11.73094670 Mar 9 5.0951256 1.0294390 23.30215254 Apr 9 -4.0353562 0.9476711 9.46565440 May 9 -6.2273339 0.9207662 -27.34799681 Jun 9 -0.4541655 0.9626983 13.10461972 Jul 9 11.7199285 1.0566189 24.10901847 Aug 9 13.0970093 1.0591463 5.84791408 Sep 9 10.0851766 1.0296366 13.91259963 Oct 9 -0.7524135 0.9522342 -33.10552086 Nov 9 -3.2885810 0.9320482 2.17802034 Dec 9 -2.1083396 0.9333400 -52.84700019 Jan 10 2.0497541 0.9496712 5.43675135 Feb 10 6.9474456 0.9717614 13.72316982 Mar 10 3.8951844 0.9457956 21.31781526 Apr 10 0.3641461 0.9135245 5.17226051 May 10 -4.4304355 0.8698789 -37.09725940 Jun 10 2.2447997 0.9148097 18.33666417 Jul 10 4.5433907 0.9252576 25.19340613 Aug 10 2.1049292 0.9011795 4.97918265 Sep 10 -2.5930758 0.8640356 14.37553818 Oct 10 -11.1077334 0.8073694 -41.69474340 Nov 10 -14.5294897 0.7842493 0.07970347 Dec 10 -26.2272962 0.7212736 -69.10425185 Jan 11 -38.8115015 0.6551871 -7.35505986 Feb 11 -35.2824473 0.6705416 27.28144359 Mar 11 -29.3319580 0.7020288 30.92101911 Apr 11 -16.2294857 0.7831360 21.83035890 May 11 -9.7444780 0.8224766 -37.44164713 Jun 11 -7.5526524 0.8320558 18.10935133 Jul 11 0.6426757 0.8825554 37.99085130 Aug 11 13.8041249 0.9629275 23.60750843 Sep 11 14.8615902 0.9635059 15.80350216 Oct 11 20.5626664 0.9902209 -30.83440051 Nov 11 6.7932143 0.9136446 -13.97167509 Dec 11 4.7845207 0.8993954 -61.60074940 Jan 12 6.1851349 0.9018156 -8.90224851 Feb 12 10.1108405 0.9172378 25.57063386 Mar 12 22.0269815 0.9783436 36.30116158 Apr 12 19.6261533 0.9580790 8.28016711 May 12 13.5016550 0.9135524 -48.73441121 Jun 12 11.1773697 0.8929089 10.92706424 Jul 12 6.8464993 0.8601288 26.39122472 Aug 12 2.7202361 0.8300820 19.59066225 Sep 12 -3.2144248 0.7916664 9.27655503 Oct 12 -7.2773340 0.7659735 -26.27954367 Nov 12 1.0527550 0.8033236 -0.38110656 Dec 12 2.9654195 0.8085397 -64.35396734 Jan 13 12.1991230 0.8478880 -0.95731404 Feb 13 -2.4573564 0.7723968 -3.18301145 Mar 13 1.2344846 0.7875983 50.30002752 Apr 13 4.2165990 0.7997671 15.35647160 May 13 -5.0272700 0.7417468 -59.86946189 Jun 13 -0.6267649 0.7631683 24.21464235 Jul 13 -2.9854745 0.7451238 24.73695949 Aug 13 2.3199419 0.7705747 30.76941562 Sep 13 -5.8533756 0.7231698 -3.56130094 Oct 13 -8.0741858 0.7084817 -30.71279237 Nov 13 -18.7908616 0.6546839 -15.14697728 Dec 13 -20.0969423 0.6458070 -63.59440112 Jan 14 -24.9062909 0.6212377 0.81703767 Feb 14 -11.2804360 0.6817156 15.77964231 Mar 14 -5.6438209 0.7060113 52.16582016 Apr 14 -2.6320465 0.7179161 20.94170132 May 14 -1.9141274 0.7179161 -62.28587700 Jun 14 1.5836598 0.7329636 29.65032570 Jul 14 9.3188269 0.7704701 32.78397125 Aug 14 9.2435059 0.7660744 32.56524808 Sep 14 11.8577150 0.7752603 2.59831319 Oct 14 13.9797295 0.7816169 -23.70812701 Nov 14 12.2219186 0.7701971 -18.58360218 Dec 14 10.7780318 0.7605543 -65.60532501 Jan 15 13.8254571 0.7704705 -3.10133925 Feb 15 11.8421165 0.7582302 7.89951850 Mar 15 7.7775030 0.7358747 45.11890079 Apr 15 -1.9460801 0.6853021 7.99066451 May 15 7.9683904 0.7312665 -47.85045987 Jun 15 10.7743065 0.7417120 25.26200820 Jul 15 -0.3263958 0.6826044 15.95304911 Aug 15 0.7986881 0.6847565 37.26836476 Sep 15 6.2172906 0.7069122 9.10549573 Oct 15 -1.6144851 0.6686728 -35.35228400 Nov 15 2.0248802 0.6814476 -9.68296630 Dec 15 -3.2998126 0.6562942 -74.79008962 Jan 16 -8.9910677 0.6298167 -6.21185798 Feb 16 1.2947192 0.6708737 27.67509562 Mar 16 1.3278716 0.6680702 44.48485518 Apr 16 1.6218031 0.6663679 3.31334880 May 16 -1.9577131 0.6465642 -52.47086792 Jun 16 1.2212744 0.6584875 36.55707693 Jul 16 7.7004721 0.6856932 22.47161349 Aug 16 4.7650296 0.6691399 28.91914242 Sep 16 2.0599461 0.6542157 10.37400290 Oct 16 -1.2304620 0.6374118 -39.51511392 Nov 16 2.5532606 0.6503648 -0.06508330 Dec 16 2.6942137 0.6483135 -74.96363889 Jan 17 6.8289532 0.6622998 -6.12798324 Feb 17 4.6755783 0.6508360 22.95981217 Mar 17 2.1075721 0.6373786 41.90301386 Apr 17 8.3672889 0.6615516 13.88321938 May 17 -2.8426485 0.6094496 -72.66473675 Jun 17 8.4883950 0.6568801 53.96366398 Jul 17 4.4966940 0.6364433 14.56003582 Aug 17 2.7200667 0.6260348 29.63718016 Sep 17 0.7234324 0.6150373 9.43616817 Oct 17 8.3666684 0.6435805 -30.44641432 Nov 17 5.0217683 0.6278430 -8.39974435 Dec 17 9.7931383 0.6438898 -68.93811770 Jan 18 3.1452197 0.6157538 -15.78486829 Feb 18 8.0461583 0.6324774 33.10879324 Mar 18 1.5978412 0.6042555 29.25174533 Apr 18 3.2543349 0.6085456 23.03794011 May 18 1.0403426 0.5968410 -81.29670514 Jun 18 2.4555304 0.6002569 59.17201143 Jul 18 5.0946995 0.6087218 18.38332003 Aug 18 5.0164131 0.6059159 28.26854448 Sep 18 5.8853076 0.6069643 7.03749468 Oct 18 7.6171438 0.6113283 -27.13120824 Nov 18 11.2882977 0.6229122 -5.67993503 Dec 18 14.3382197 0.6319554 -63.42186471 Jan 19 19.3206107 0.6481072 -12.06432317 Feb 19 8.6570505 0.6057459 19.47291626 Mar 19 4.7664308 0.5886241 27.68278526 Apr 19 -4.7056040 0.5496059 12.83171837 May 19 -3.6847413 0.5514590 -76.89090877 Jun 19 -3.3865067 0.5504580 57.94957788 Jul 19 -0.9835634 0.5577468 21.22690383 Aug 19 0.9631885 0.5631356 28.84417704 Sep 19 0.7307335 0.5601123 4.21101502 Oct 19 5.4715810 0.5756343 -22.87324784 Nov 19 4.3508600 0.5694659 -10.51513462 Dec 19 7.0369292 0.5770580 -59.47627021 Jan 20 6.4029763 0.5727295 -7.16417800 Feb 20 4.8797162 0.5651892 21.12912318 Mar 20 2.7759867 0.5554605 30.05431615 Apr 20 4.2941972 0.5590219 14.92441112 May 20 -6.8492905 0.5152444 -93.36123840 Jun 20 -10.9557124 0.4978824 55.48664642 Jul 20 -5.5967844 0.5160663 29.32117091 Aug 20 -9.5823799 0.4994299 20.74399649 Sep 20 -9.3079867 0.4986130 3.93109609 Oct 20 0.5650321 0.5319771 -9.12839895 Nov 20 9.5913936 0.5616762 -3.49303703 Dec 20 14.4820043 0.5766339 -56.10060427 Jan 21 7.4101631 0.5502980 -17.72369386 Feb 21 8.3383946 0.5516055 26.91881904 Mar 21 9.7196962 0.5545058 32.88893429 Apr 21 6.9210734 0.5426464 16.59291323 May 21 -5.2705882 0.4972010 -107.54860047 Jun 21 -8.5310993 0.4837474 53.72569651 Jul 21 -2.8042000 0.5024473 39.77601640 Aug 21 -1.7081438 0.5045422 17.35564773 Sep 21 2.3993794 0.5170653 2.12504541 Oct 21 4.4161012 0.5221897 -13.17077682 Nov 21 9.1204862 0.5362642 0.66973951 Dec 21 9.2254343 0.5348275 -54.30560503 Jan 22 10.4741004 0.5371971 -16.29988519 Feb 22 5.4335104 0.5186189 20.18078405 Mar 22 -0.5709467 0.4967175 30.44202849 Apr 22 -0.6123228 0.4948940 25.58525128 May 22 -0.8007976 0.4925616 -107.21765667 Jun 22 -8.1673596 0.4656741 40.25603663 Jul 22 -8.5390968 0.4628193 40.94207765 Aug 22 -12.3953459 0.4482290 9.80099187 Sep 22 -6.4291840 0.4666254 10.29943657 Oct 22 3.5542151 0.4978928 -4.23307560 Nov 22 5.8751772 0.5038043 -0.19587387 Dec 22 -1.5698931 0.4782607 -64.90291441 Jan 23 -8.7415305 0.4537597 -19.06143021 Feb 23 -11.7615654 0.4426087 22.85482796 Mar 23 -12.3375569 0.4393189 31.90153169 Apr 23 -11.7202407 0.4398979 28.26444066 May 23 -15.0427297 0.4275895 -108.05058048 Jun 23 -17.7593807 0.4172862 38.17789678 Jul 23 -16.5114777 0.4199992 44.31770144 Aug 23 -15.1810410 0.4229491 6.67235428 Sep 23 -11.4993999 0.4333882 10.11450585 Oct 23 -16.1669938 0.4172522 -11.29844138 Nov 23 -14.4156510 0.4214246 9.59719930 Dec 23 -14.8497287 0.4187702 -61.71998790 Jan 24 -7.0096956 0.4417216 -6.46247859 Feb 24 -3.2155726 0.4521037 25.09496922 Mar 24 2.4812421 0.4684211 38.07776189 Apr 24 2.6485070 0.4674789 27.78447205 May 24 1.5563163 0.4625784 -108.91401665 Jun 24 -4.3257286 0.4426228 29.44747306 Jul 24 -7.9655253 0.4298219 40.73534599 Aug 24 -1.7078027 0.4479679 15.42726863 Sep 24 3.5936857 0.4629315 16.42599700 Oct 24 0.4453038 0.4519187 -19.75088564 Nov 24 1.2665547 0.4530339 10.20216080 Dec 24 -1.0052329 0.4448641 -70.27496010 Jan 25 2.5482572 0.4541551 -3.52013598 Feb 25 1.7277008 0.4503427 19.80592911 Mar 25 4.8465523 0.4583506 43.11514097 Apr 25 5.6702614 0.4594516 29.10424668 May 25 3.8531460 0.4525692 -108.77885132 Jun 25 1.5992815 0.4443830 27.59336407 Jul 25 -0.2773486 0.4373830 35.21587379 Aug 25 1.4996072 0.4413980 16.47336972 Sep 25 1.6744391 0.4406059 17.50906898 Oct 25 12.0955983 0.4699829 -6.05607469 Nov 25 11.4164666 0.4666297 5.23705593 Dec 25 12.8943330 0.4695620 -70.24950687 Jan 26 6.3376225 0.4492504 -13.22683804 Feb 26 8.0754675 0.4529759 23.37031572 Mar 26 3.8065592 0.4392921 36.78764018 Apr 26 4.3474515 0.4395875 33.00636454 May 26 4.1375065 0.4376951 -108.00296227 Jun 26 3.6635043 0.4350386 27.34826991 Jul 26 2.9828063 0.4317965 32.82263795 Aug 26 -0.4646185 0.4205869 10.34693657 Sep 26 6.7451319 0.4400577 23.68413408 Oct 26 -0.3714263 0.4185650 -18.05240464 Nov 26 -2.4381910 0.4115497 5.81553332 Dec 26 -9.3646523 0.3909538 -75.07279358 Jan 27 -7.5408496 0.3949634 -7.72163618 Feb 27 -1.8721354 0.4097161 32.78113039 Mar 27 1.7123699 0.4186109 39.11802007 Apr 27 -2.7857602 0.4048054 25.56242903 May 27 -6.6371522 0.3928365 -110.83695154 Jun 27 -9.4625205 0.3837892 26.09454115 Jul 27 -6.2953518 0.3915934 39.78898473 Aug 27 -14.6785370 0.3671122 -4.39024583 Sep 27 -14.8803703 0.3655354 31.49942711 Oct 27 -23.5682466 0.3406266 -27.49745560 Nov 27 -31.6475814 0.3176159 1.67056529 Dec 27 -58.5792611 0.2435265 -109.58627739 Jan 28 -46.8589497 0.2746408 17.43422462 Feb 28 -43.1687624 0.2838941 33.25100545 Mar 28 -28.3039308 0.3234307 61.21059650 Apr 28 -21.3086675 0.3415477 31.40289414 May 28 -10.8958119 0.3689201 -98.20430338 Jun 28 -4.1373874 0.3862758 30.93795116 Jul 28 -0.4879766 0.3951168 47.08960183 Aug 28 5.2940618 0.4096466 4.34919600 Sep 28 1.9197665 0.3995005 31.32917687 Oct 28 6.9192104 0.4117554 -12.24362525 Nov 28 3.5412377 0.4017192 5.51664236 Dec 28 7.7987666 0.4118831 -111.25196911 Jan 29 7.0514699 0.4088360 8.71801104 Feb 29 12.6452327 0.4224516 30.68737323 Mar 29 12.4050407 0.4207110 52.04929050 Apr 29 18.3805649 0.4353149 32.21956625 May 29 5.9106296 0.4013732 -122.42489150 Jun 29 -2.2068025 0.3789868 22.27554695 Jul 29 -7.4495688 0.3642498 41.04629392 Aug 29 0.3532000 0.3836699 18.53292936 Sep 29 -1.3140526 0.3783436 23.56821249 Oct 29 -4.8998259 0.3681074 -15.58993194 Nov 29 -2.7840889 0.3725961 7.56655258 Dec 29 5.9517017 0.3939855 -100.59955421 Jan 30 -2.9389628 0.3703040 -9.78564118 Feb 30 3.3890123 0.3854813 43.32845245 Mar 30 15.6776698 0.4158021 65.97496618 Apr 30 13.5192717 0.4092427 31.88901660 May 30 6.7209603 0.3908777 -126.53802120 Jun 30 11.5709788 0.4022280 33.20523246 Jul 30 4.2163969 0.3825309 25.35834416 Aug 30 5.7102273 0.3853424 24.68872377 Sep 30 3.7164679 0.3793520 21.31127179 Oct 30 4.0981026 0.3793577 -16.60139174 Nov 30 14.4839096 0.4043042 17.69789099 Dec 30 10.9938481 0.3946332 -107.08235988 Jan 31 16.0063886 0.4060708 -6.86051167 Feb 31 9.4202406 0.3887763 26.65511276 Mar 31 9.2474034 0.3873878 70.66184222 Apr 31 3.7425553 0.3728218 27.84771533 May 31 13.0531462 0.3949084 -112.83186549 Jun 31 -1.8390873 0.3571765 12.66719451 Jul 31 4.0137910 0.3707097 38.76691105 Aug 31 0.6144246 0.3614578 18.21845789 Sep 31 3.9419196 0.3687055 25.48368007 Oct 31 4.6001821 0.3694098 -21.91748385 Nov 31 -3.9830420 0.3477286 7.28575838 > m$resid Jan Feb Mar Apr May 1 0.000000e+00 2.793417e+00 2.176267e+00 1.741778e+00 -2.484617e+00 2 -3.021041e-01 1.038914e+00 9.432810e-01 -1.297393e+00 -1.059830e+00 3 6.207105e-01 2.023238e+00 2.260785e+00 8.479585e-01 -1.645707e+00 4 6.618667e-01 -4.649211e-01 -7.438173e-03 -3.677664e-01 -7.504136e-01 5 -2.359409e-01 6.531094e-01 -6.248019e-01 -4.237373e-01 3.365043e-01 6 8.395585e-01 -6.036163e-01 -7.863607e-01 5.406330e-01 3.549032e-01 7 -9.184420e-01 4.102039e-01 1.644172e+00 1.312659e+00 1.736686e+00 8 5.641317e-02 7.516082e-02 -6.245256e-01 1.015068e+00 -5.083650e-01 9 -3.108122e-01 -9.445132e-01 1.060022e+00 -1.505419e+00 -4.651459e-01 10 4.834357e-01 5.901703e-01 -5.994754e-01 -6.654912e-01 -8.482915e-01 11 -1.995252e+00 4.300551e-01 7.881559e-01 1.848004e+00 8.494746e-01 12 7.519287e-02 4.529383e-01 1.644498e+00 -5.046004e-01 -1.057309e+00 13 1.264550e+00 -2.324358e+00 4.370819e-01 3.282339e-01 -1.501840e+00 14 -8.191854e-01 1.951133e+00 7.426497e-01 3.453373e-01 4.600485e-07 15 3.435846e-01 -4.134587e-01 -7.235490e-01 -1.568295e+00 1.383576e+00 16 -9.541343e-01 1.450688e+00 -9.575367e-02 -5.615231e-02 -6.371476e-01 17 5.243083e-01 -4.232685e-01 -4.836587e-01 8.445204e-01 -1.782988e+00 18 -1.097071e+00 6.445194e-01 -1.064632e+00 1.581681e-01 -4.242339e-01 19 6.548090e-01 -1.702184e+00 -6.764365e-01 -1.513230e+00 7.087708e-02 20 -1.823485e-01 -3.155476e-01 -4.017198e-01 1.448887e-01 -1.761071e+00 21 -1.152102e+00 5.692089e-02 1.249418e-01 -5.048794e-01 -1.917325e+00 22 1.075644e-01 -8.403978e-01 -9.827064e-01 -8.105690e-02 -1.029378e-01 23 -1.153101e+00 -5.235781e-01 -1.535118e-01 2.682389e-02 -5.669740e-01 24 1.118985e+00 5.054481e-01 7.907012e-01 -4.540049e-02 -2.351232e-01 25 4.688580e-01 -1.922498e-01 4.024392e-01 5.509782e-02 -3.433147e-01 26 -1.060027e+00 1.943992e-01 -7.123234e-01 1.532655e-02 -9.798273e-02 27 2.162243e-01 7.958185e-01 4.790684e-01 -7.419110e-01 -6.422383e-01 28 1.732327e+00 5.155413e-01 2.200800e+00 1.007012e+00 1.520116e+00 29 -1.750089e-01 7.827950e-01 -1.000415e-01 8.386220e-01 -1.948342e+00 30 -1.402068e+00 8.996591e-01 1.797468e+00 -3.887219e-01 -1.088397e+00 31 6.974893e-01 -1.056104e+00 -8.482577e-02 -8.899595e-01 1.349964e+00 Jun Jul Aug Sep Oct 1 -5.051909e-01 4.594443e-01 2.576418e-01 5.876161e-01 -2.370606e+00 2 -1.369547e+00 2.371768e+00 1.748538e+00 -1.262571e+00 8.346147e-01 3 4.210639e-01 9.408662e-01 -1.247445e+00 6.507779e-01 -3.042527e+00 4 -7.045882e-02 -8.048587e-01 -7.482744e-01 -4.575923e-01 -7.832195e-01 5 -4.063697e-01 -7.853474e-01 7.130954e-01 7.062455e-02 -1.793805e-01 6 -5.031853e-02 -4.353970e-01 -1.017898e+00 -7.136063e-01 -1.219961e+00 7 3.129920e-01 -1.509964e-01 -1.340911e-01 9.704248e-01 -5.195958e-01 8 5.817331e-01 -8.855158e-01 2.170438e-01 -1.672144e+00 -5.855361e-01 9 7.201569e-01 1.668178e+00 4.780607e-02 -6.086547e-01 -1.777369e+00 10 8.637860e-01 2.062951e-01 -5.025038e-01 -8.379936e-01 -1.405678e+00 11 2.041793e-01 1.099541e+00 1.836604e+00 1.416166e-02 7.105287e-01 12 -4.836404e-01 -7.811677e-01 -7.466477e-01 -1.014175e+00 -7.285124e-01 13 5.473311e-01 -4.674237e-01 6.835045e-01 -1.341863e+00 -4.420416e-01 14 4.163822e-01 1.049530e+00 -1.268777e-01 2.774645e-01 2.023229e-01 15 3.110884e-01 -1.776673e+00 6.642773e-02 7.111411e-01 -1.283404e+00 16 3.800864e-01 8.739787e-01 -5.440028e-01 -5.071796e-01 -5.931736e-01 17 1.610494e+00 -6.984920e-01 -3.627412e-01 -3.944196e-01 1.057336e+00 18 1.230119e-01 3.065636e-01 -1.033317e-01 3.956812e-02 1.692989e-01 19 -3.808808e-02 2.786942e-01 2.090249e-01 -1.197592e-01 6.294704e-01 20 -6.955447e-01 7.316925e-01 -6.777507e-01 -3.388851e-02 1.411979e+00 21 -5.658058e-01 7.895782e-01 8.940942e-02 5.427858e-01 2.259585e-01 22 -1.183896e+00 -1.261614e-01 -6.507937e-01 8.315696e-01 1.434400e+00 23 -4.738407e-01 1.251864e-01 1.372336e-01 4.912591e-01 -7.690769e-01 24 -9.564967e-01 -6.155003e-01 8.787543e-01 7.319131e-01 -5.446389e-01 25 -4.081523e-01 -3.500501e-01 2.020487e-01 -4.021002e-02 1.505630e+00 26 -1.375342e-01 -1.683237e-01 -5.852740e-01 1.024387e+00 -1.140261e+00 27 -4.856221e-01 4.200269e-01 -1.324241e+00 -8.586764e-02 -1.366457e+00 28 9.644226e-01 4.925523e-01 8.131680e-01 -5.712258e-01 6.944437e-01 29 -1.286134e+00 -8.487778e-01 1.123124e+00 -3.096783e-01 -5.985857e-01 30 6.733772e-01 -1.171395e+00 1.678293e-01 -3.593082e-01 3.447722e-04 31 -2.309016e+00 8.301092e-01 -5.694773e-01 4.480413e-01 4.374107e-02 Nov Dec 1 -1.554596e+00 -3.826951e+00 2 -1.278596e+00 -3.776878e+00 3 -1.691603e+00 1.721256e-01 4 4.665450e-01 -5.918689e-01 5 -7.504863e-01 -1.037377e+00 6 -1.605450e+00 -2.265773e+00 7 -3.472281e-01 -4.959278e-01 8 -7.580945e-01 7.728889e-01 9 -5.231107e-01 3.723867e-02 10 -6.344804e-01 -1.873225e+00 11 -2.215323e+00 -4.387015e-01 12 1.135818e+00 1.665948e-01 13 -1.716333e+00 -2.945731e-01 14 -3.816471e-01 -3.327660e-01 15 4.466497e-01 -9.030646e-01 16 4.732486e-01 -7.662464e-02 17 -6.001610e-01 6.235069e-01 18 4.605990e-01 3.653493e-01 19 -2.554477e-01 3.187388e-01 20 1.279583e+00 6.521207e-01 21 6.302099e-01 -6.499602e-02 22 2.748027e-01 -1.198212e+00 23 2.011560e-01 -1.289967e-01 24 5.570418e-02 -4.109776e-01 25 -1.733606e-01 1.525629e-01 26 -3.750430e-01 -1.107349e+00 27 -1.270900e+00 -4.113061e+00 28 -5.721476e-01 5.821351e-01 29 2.639022e-01 1.262913e+00 30 1.511340e+00 -5.882017e-01 31 -1.352437e+00 > mylevel <- as.numeric(m$fitted[,'level']) > myslope <- as.numeric(m$fitted[,'slope']) > myseas <- as.numeric(m$fitted[,'sea']) > myresid <- as.numeric(m$resid) > myfit <- mylevel+myseas > postscript(file="/var/wessaorg/rcomp/tmp/19gzm1322150041.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time') > grid() > dev.off() null device 1 > mylagmax <- nx/2 > postscript(file="/var/wessaorg/rcomp/tmp/278cq1322150041.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/3ecb01322150041.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/4vbj01322150041.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/58bgn1322150041.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/6oanq1322150041.tab") > > try(system("convert tmp/19gzm1322150041.ps tmp/19gzm1322150041.png",intern=TRUE)) character(0) > try(system("convert tmp/278cq1322150041.ps tmp/278cq1322150041.png",intern=TRUE)) character(0) > try(system("convert tmp/3ecb01322150041.ps tmp/3ecb01322150041.png",intern=TRUE)) character(0) > try(system("convert tmp/4vbj01322150041.ps tmp/4vbj01322150041.png",intern=TRUE)) character(0) > try(system("convert tmp/58bgn1322150041.ps tmp/58bgn1322150041.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.850 0.406 6.891