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(348542 + ,335658 + ,330664 + ,326814 + ,322900 + ,322310 + ,385164 + ,404861 + ,412136 + ,411057 + ,410040 + ,414980 + ,413626 + ,411062 + ,408352 + ,409780 + ,411318 + ,415555 + ,479481 + ,497826 + ,501638 + ,497990 + ,499287 + ,506247 + ,510401 + ,508642 + ,501805 + ,495476 + ,490336 + ,490042 + ,553155 + ,569999 + ,573170 + ,571687 + ,575453 + ,580177 + ,579849 + ,574346 + ,563325 + ,555604 + ,545544 + ,545109 + ,605181 + ,627856 + ,631421 + ,625671 + ,613577 + ,606463 + ,601676 + ,589121 + ,573559 + ,558487 + ,552148 + ,545720 + ,606569 + ,636067 + ,630704 + ,623275 + ,617771 + ,605401 + ,619393 + ,596019 + ,569977 + ,546213 + ,528492 + ,505944 + ,554910 + ,567831 + ,564021 + ,552800 + ,541102 + ,542378 + ,540380 + ,521219 + ,504652 + ,490626 + ,481686 + ,477930 + ,522605 + ,531432 + ,532355 + ,539954 + ,524987 + ,533307 + ,530541 + ,508392 + ,495208 + ,482223 + ,470495 + ,466106 + ,515037 + ,517752 + ,515565 + ,510727 + ,499725 + ,498369 + ,493756 + ,476141 + ,458458 + ,443182 + ,429597 + ,424476 + ,476257 + ,480555 + ,469762 + ,459820 + ,451028 + ,450065 + ,444385 + ,428846 + ,421020 + ,399778 + ,389005 + ,384018 + ,431933 + ,445844 + ,431464 + ,423263 + ,415881 + ,416208 + ,413491 + ,399153 + ,385939 + ,373917 + ,364635 + ,364696 + ,418358 + ,428212 + ,423730 + ,420677 + ,417428 + ,423245 + ,423113 + ,418873 + ,405733 + ,397812 + ,389918 + ,391116 + ,443814 + ,460373 + ,455422 + ,456288 + ,452233 + ,459256 + ,461146 + ,451391 + ,443101 + ,438810 + ,430457 + ,435721 + ,488280 + ,505814 + ,502338 + ,500910 + ,501434 + ,515476 + ,520862 + ,519517 + ,511805 + ,508607 + ,505327 + ,511435 + ,570158 + ,591665 + ,593572 + ,586346 + ,586063 + ,591504 + ,594033 + ,585597 + ,572450 + ,562917 + ,554675 + ,553997 + ,601310 + ,622255 + ,616735 + ,606480 + ,595079 + ,598588 + ,599917 + ,591573 + ,575489 + ,567223 + ,555338 + ,555252 + ,608249 + ,630859 + ,628632 + ,624435 + ,609670 + ,615830 + ,621170 + ,604212 + ,584348 + ,573717 + ,555234 + ,544897 + ,598866 + ,620081 + ,607699 + ,589960 + ,578665 + ,580166 + ,579457 + ,571560 + ,560460 + ,551397 + ,536763 + ,540562 + ,588184 + ,607049 + ,598968 + ,577644 + ,562640 + ,565867 + ,561274 + ,554144 + ,539900 + ,526271 + ,511841 + ,505282 + ,554083 + ,584225 + ,568858 + ,539516 + ,521612 + ,525562 + ,526519 + ,515713 + ,503454 + ,489301 + ,479020 + ,475102 + ,523682 + ,551528 + ,531626 + ,511037 + ,492417 + ,492188 + ,492865 + ,480961 + ,461935 + ,456608 + ,441977 + ,439148 + ,488180 + ,520564 + ,501492 + ,485025 + ,464196 + ,460170 + ,467037 + ,460070 + ,447988 + ,442867 + ,436087 + ,431328 + ,484015 + ,509673 + ,512927 + ,502831 + ,470984 + ,471067 + ,476049 + ,474605 + ,470439 + ,461251 + ,454724 + ,455626 + ,516847 + ,525192 + ,522975 + ,518585 + ,509239 + ,512238 + ,519164 + ,517009 + ,509933 + ,509127 + ,500857 + ,506971 + ,569323 + ,579714 + ,577992 + ,565464 + ,547344 + ,554788 + ,562325 + ,560854 + ,555332 + ,543599 + ,536662 + ,542722 + ,593530 + ,610763 + ,612613 + ,611324 + ,594167 + ,595454 + ,590865 + ,589379 + ,584428 + ,573100 + ,567456 + ,569028 + ,620735 + ,628884 + ,628232 + ,612117 + ,595404 + ,597141) > 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 0 30724597 8468737 0 > m$fitted level slope sea Jan 1 348542.0 0.00000 0.00000 Feb 1 339556.7 -9307.51147 -3898.69466 Mar 1 328485.6 -10486.91810 2178.40025 Apr 1 324254.3 -6053.80352 2559.71504 May 1 322175.7 -3280.57520 724.30902 Jun 1 321670.5 -1364.97009 639.53654 Jul 1 369514.9 32723.73126 15649.09368 Aug 1 407885.3 36640.11494 -3024.28620 Sep 1 420376.3 19891.29933 -8240.25551 Oct 1 416262.9 3246.30785 -5205.90135 Nov 1 410454.3 -3031.57776 -414.26255 Dec 1 412387.7 410.66176 2592.33317 Jan 2 413931.3 1193.80776 -305.25672 Feb 2 414577.4 813.66054 -3515.38089 Mar 2 408782.4 -3626.82090 -430.44250 Apr 2 404537.8 -4038.76472 5242.21294 May 2 407732.1 831.08657 3585.94507 Jun 2 426509.8 12817.96505 -10954.79573 Jul 2 461818.4 27808.50870 17662.56801 Aug 2 494616.9 31140.80737 3209.13736 Sep 2 508640.2 19701.35121 -7002.16015 Oct 2 506537.9 5130.26310 -8547.87892 Nov 2 502977.6 -674.86528 -3690.63749 Dec 2 503527.3 142.17193 2719.69312 Jan 3 508644.1 3461.99616 1756.86392 Feb 3 509625.0 1804.07112 -983.01475 Mar 3 502366.0 -4195.48296 -561.04050 Apr 3 492184.3 -8141.49621 3291.65948 May 3 490550.6 -3828.76912 -214.57861 Jun 3 504912.5 8205.93239 -14870.51968 Jul 3 533374.3 21567.03374 19780.71114 Aug 3 560834.4 25456.52561 9164.64987 Sep 3 576331.0 18876.25947 -3161.04521 Oct 3 581402.8 9754.56586 -9715.76204 Nov 3 582564.0 4079.12064 -7110.97362 Dec 3 581408.4 623.75266 -1231.38512 Jan 4 578155.8 -1936.90787 1693.18929 Feb 4 571854.7 -4819.06461 2491.30122 Mar 4 561190.8 -8661.26871 2134.18028 Apr 4 552608.3 -8609.63357 2995.73947 May 4 550095.3 -4599.00243 -4551.27140 Jun 4 562737.7 6745.10927 -17628.73259 Jul 4 584513.7 16614.93936 20667.34940 Aug 4 612844.9 24305.80238 15011.12180 Sep 4 632518.7 21263.21138 -1097.67732 Oct 4 637992.5 10889.33918 -12321.46594 Nov 4 626303.2 -3941.28033 -12726.21622 Dec 4 609908.8 -12120.92440 -3445.76782 Jan 5 597637.6 -12219.63914 4038.35645 Feb 5 583762.4 -13307.04994 5358.63228 Mar 5 569443.3 -13969.92724 4115.72143 Apr 5 555817.3 -13744.90728 2669.71439 May 5 557273.3 -3783.47516 -5125.26700 Jun 5 566380.1 4668.75148 -20660.08729 Jul 5 587168.7 15226.02622 19400.29506 Aug 5 617184.4 24905.40799 18882.55149 Sep 5 631238.3 17802.01163 -534.27945 Oct 5 632653.5 7073.13319 -9378.49050 Nov 5 629352.8 281.13849 -11581.83072 Dec 5 613731.0 -10133.42792 -8329.95327 Jan 6 610929.8 -5329.94226 8463.21006 Feb 6 593064.0 -13536.43176 2955.00341 Mar 6 567327.6 -21508.42815 2649.42207 Apr 6 546489.5 -21070.66413 -276.54687 May 6 534986.1 -14816.65572 -6494.06472 Jun 6 530767.5 -7884.35723 -24823.53107 Jul 6 537577.3 1720.27435 17332.73821 Aug 6 544886.9 5370.83489 22944.06026 Sep 6 557479.1 10086.46249 6541.92937 Oct 6 561197.7 5927.65345 -8397.69619 Nov 6 552909.5 -3358.33496 -11807.49528 Dec 6 552276.8 -1577.31056 -9898.79177 Jan 7 532980.2 -13157.82299 7399.76206 Feb 7 513776.2 -17106.51535 7442.75811 Mar 7 499835.0 -15042.03967 4816.96899 Apr 7 491248.5 -10833.58385 -622.45375 May 7 488960.6 -5258.08202 -7274.62542 Jun 7 502222.3 6831.81570 -24292.28895 Jul 7 509052.3 6830.64770 13552.68534 Aug 7 512656.4 4726.90315 18775.58324 Sep 7 522364.5 7973.48081 9990.48037 Oct 7 541648.0 15345.27638 -1693.98959 Nov 7 542820.8 6105.14959 -17833.84064 Dec 7 538753.9 -529.33476 -5446.91221 Jan 8 524269.4 -9631.91132 6271.64209 Feb 8 503850.1 -16663.38030 4541.86302 Mar 8 490338.5 -14611.08872 4869.46517 Apr 8 483784.5 -9366.39108 -1561.52961 May 8 481866.7 -4514.89314 -11371.65573 Jun 8 486886.9 1698.92829 -20780.85125 Jul 8 497902.3 7768.54227 17134.68760 Aug 8 503443.4 6318.46944 14308.55501 Sep 8 510212.2 6611.47984 5352.78340 Oct 8 510602.8 2563.61842 124.19160 Nov 8 513740.6 2937.32113 -14015.55685 Dec 8 502763.3 -6123.18612 -4394.28359 Jan 9 485636.9 -13287.96149 8119.12081 Feb 9 471711.4 -13702.85024 4429.64802 Mar 9 456309.6 -14807.44086 2148.37531 Apr 9 445621.2 -12129.95227 -2439.20137 May 9 442061.3 -6556.35633 -12464.33703 Jun 9 445765.9 119.99748 -21289.88907 Jul 9 456076.7 6749.37217 20180.33455 Aug 9 466269.7 8988.04771 14285.33428 Sep 9 466344.7 3196.83650 3417.26598 Oct 9 462137.3 -1613.82058 -2317.34142 Nov 9 459995.2 -1957.22765 -8967.15200 Dec 9 452371.8 -5641.23933 -2306.77671 Jan 10 437809.1 -11441.56558 6575.88662 Feb 10 423372.3 -13387.82519 5473.74010 Mar 10 417188.7 -8710.02591 3831.29014 Apr 10 406060.6 -10279.79133 -6282.62876 May 10 402962.3 -5615.75054 -13957.25401 Jun 10 407036.1 679.88865 -23018.11078 Jul 10 412283.4 3647.03735 19649.58813 Aug 10 425706.5 9994.03749 20137.52546 Sep 10 428768.8 5496.03223 2695.22803 Oct 10 427431.6 1062.31062 -4168.63800 Nov 10 423814.1 -1975.24607 -7933.07059 Dec 10 416504.1 -5439.03812 -296.12911 Jan 11 406864.3 -8166.47566 6626.73709 Feb 11 395988.5 -9924.54044 3164.46995 Mar 11 381814.1 -12680.59991 4124.85655 Apr 11 379098.0 -6219.55996 -5181.02295 May 11 380229.1 -1451.62917 -15594.06331 Jun 11 387688.1 4330.38959 -22992.10197 Jul 11 400334.4 9725.87102 18023.58836 Aug 11 407204.6 7874.09457 21007.36888 Sep 11 417876.6 9687.51092 5853.36942 Oct 11 424592.3 7761.49520 -3915.26332 Nov 11 425516.0 3328.68582 -8087.97178 Dec 11 423178.5 -345.78745 66.51802 Jan 12 416328.1 -4563.71935 6784.88601 Feb 12 412989.7 -3769.58411 5883.34436 Mar 12 405778.7 -5998.82922 -45.72540 Apr 12 403914.8 -3320.68267 -6102.76541 May 12 407153.2 928.98786 -17235.16236 Jun 12 415142.1 5504.67187 -24026.05359 Jul 12 424448.8 7968.68035 19365.17045 Aug 12 438977.5 12217.88241 21395.53231 Sep 12 449664.3 11226.60698 5757.70906 Oct 12 458544.9 9707.85028 -2256.92515 Nov 12 460464.2 4664.19041 -8231.22206 Dec 12 458517.1 381.61316 738.87923 Jan 13 455091.8 -2084.24486 6054.18631 Feb 13 445857.1 -6713.76634 5533.92070 Mar 13 442728.2 -4393.85359 372.75964 Apr 13 445179.7 35.43591 -6369.67628 May 13 449169.1 2594.61882 -18712.10379 Jun 13 459297.2 7472.04728 -23576.20655 Jul 13 470781.4 10069.48062 17498.55966 Aug 13 483737.8 11937.62096 22076.15594 Sep 13 496077.2 12197.48309 6260.78518 Oct 13 502414.6 8407.33988 -1504.60018 Nov 13 507916.6 6527.79135 -6482.64203 Dec 13 513062.3 5633.40287 2413.68517 Jan 14 513401.2 2207.44491 7460.77224 Feb 14 514851.6 1717.75008 4665.40761 Mar 14 514164.7 163.01510 -2359.65730 Apr 14 515733.8 1072.04117 -7126.78831 May 14 524481.9 6035.71051 -19154.89408 Jun 14 535592.7 9318.36346 -24157.71227 Jul 14 552074.4 13951.39446 18083.64741 Aug 14 569174.0 15986.84582 22490.95864 Sep 14 585410.1 16147.90088 8161.90692 Oct 14 590459.9 8976.06636 -4113.88198 Nov 14 593248.3 4976.53618 -7185.27623 Dec 14 589616.2 -589.15844 1887.76157 Jan 15 586302.0 -2350.88654 7730.95131 Feb 15 580519.9 -4568.37655 5077.06980 Mar 15 575116.2 -5108.06162 -2666.15572 Apr 15 571911.9 -3878.30162 -8994.85021 May 15 574112.6 49.43645 -19437.61889 Jun 15 579852.3 3726.84534 -25855.33677 Jul 15 585027.7 4662.91971 16282.29922 Aug 15 597713.7 9845.90060 24541.27745 Sep 15 605951.3 8807.29359 10783.67336 Oct 15 609741.1 5567.33368 -3261.12352 Nov 15 602822.2 -2497.12430 -7743.17536 Dec 15 596152.7 -5192.50729 2435.32059 Jan 16 590635.7 -5402.08918 9281.26803 Feb 16 585686.6 -5109.58711 5886.40922 Mar 16 579091.2 -6068.72833 -3602.24625 Apr 16 576946.5 -3535.79669 -9723.45996 May 16 576064.0 -1822.70953 -20726.00768 Jun 16 580479.3 2205.58308 -25227.27608 Jul 16 592720.4 8685.96439 15528.57637 Aug 16 605549.1 11360.25436 25309.93199 Sep 16 616189.9 10895.98995 12442.08377 Oct 16 623940.6 8866.34892 494.36434 Nov 16 619686.0 397.86967 -10016.04499 Dec 16 614230.0 -3381.10775 1600.03065 Jan 17 611325.0 -3073.77373 9845.03535 Feb 17 600097.5 -8335.62870 4114.45580 Mar 17 589108.4 -10047.54433 -4760.38180 Apr 17 582814.3 -7626.19407 -9097.28185 May 17 577883.8 -5886.88661 -22649.80264 Jun 17 573760.7 -4748.68028 -28863.66847 Jul 17 581667.6 3418.09926 17198.40468 Aug 17 593430.0 8801.34317 26650.96073 Sep 17 596256.5 4947.80818 11442.48404 Oct 17 588310.9 -3367.35269 1649.06051 Nov 17 585983.1 -2696.87611 -7318.05213 Dec 17 579780.8 -4958.31918 385.21454 Jan 18 568172.6 -9248.24457 11284.42025 Feb 18 564268.2 -5801.69974 7291.78505 Mar 18 564602.7 -1845.21213 -4142.67644 Apr 18 561474.1 -2672.61981 -10077.14894 May 18 559884.3 -1974.42513 -23121.27044 Jun 18 570946.2 6433.31308 -30384.18779 Jul 18 575671.0 5331.46720 12512.98155 Aug 18 578481.4 3705.90505 28567.64433 Sep 18 582846.8 4131.07230 16121.17319 Oct 18 578837.1 -1116.33700 -1193.07705 Nov 18 569947.2 -6127.70590 -7307.20991 Dec 18 562909.8 -6714.23188 2957.16248 Jan 19 553013.7 -8765.78359 8260.31354 Feb 19 547466.4 -6691.12808 6677.63884 Mar 19 542782.0 -5397.87101 -2881.95627 Apr 19 537423.5 -5372.44529 -11152.54006 May 19 537968.6 -1558.51276 -26127.64667 Jun 19 535857.1 -1915.02899 -30575.05740 Jul 19 539528.0 1685.63653 14554.98750 Aug 19 552821.3 9166.27702 31403.67795 Sep 19 553003.1 3377.41058 15854.90705 Oct 19 541650.0 -6113.24079 -2133.95107 Nov 19 529333.9 -10110.13006 -7721.85955 Dec 19 520796.3 -9096.70925 4765.73699 Jan 20 517697.5 -5231.42826 8821.52001 Feb 20 510415.0 -6552.91959 5297.95880 Mar 20 505567.8 -5454.14430 -2113.81552 Apr 20 501725.1 -4416.12791 -12424.12502 May 20 503354.6 -521.42768 -24334.56843 Jun 20 507801.6 2679.76221 -32699.57021 Jul 20 513181.2 4419.26212 10500.80690 Aug 20 516878.5 3954.21736 34649.46634 Sep 20 512470.9 -1431.25742 19155.09653 Oct 20 510413.4 -1834.56347 623.58272 Nov 20 502711.2 -5613.85174 -10294.24327 Dec 20 490862.3 -9630.29584 1325.67264 Jan 21 482412.2 -8870.05352 10452.75753 Feb 21 475491.4 -7614.68327 5469.62845 Mar 21 465453.9 -9174.77745 -3518.93392 Apr 21 467747.7 -1790.09106 -11139.73847 May 21 468474.5 -169.28992 -26497.53298 Jun 21 472126.8 2291.98615 -32978.84263 Jul 21 476843.0 3853.19917 11337.04757 Aug 21 482759.3 5181.73128 37804.68759 Sep 21 483506.7 2326.80938 17985.28767 Oct 21 482603.6 247.38403 2421.42347 Nov 21 474488.5 -5136.85313 -10292.48257 Dec 21 461080.1 -10463.06323 -910.14696 Jan 22 454906.6 -7700.96886 12130.37722 Feb 22 452626.5 -4210.95505 7443.54962 Mar 22 454054.5 -581.00027 -6066.53907 Apr 22 454802.1 274.19592 -11935.11665 May 22 462026.3 4748.25862 -25939.31632 Jun 22 466199.6 4378.08314 -34871.60158 Jul 22 472894.3 5869.51190 11120.72583 Aug 22 472662.0 1941.67653 37011.03564 Sep 22 488880.1 11130.28263 24046.92445 Oct 22 498138.3 9925.40374 4692.74373 Nov 22 484725.2 -5096.39585 -13741.19173 Dec 22 473658.7 -8939.39587 -2591.70907 Jan 23 465501.6 -8435.84695 10547.41474 Feb 23 466372.4 -2445.92671 8232.62285 Mar 23 474595.7 4420.07584 -4156.74193 Apr 23 476804.6 2997.15125 -15553.61478 May 23 480076.7 3174.06016 -25352.65869 Jun 23 489089.5 6931.99405 -33463.53754 Jul 23 503070.0 11468.44625 13776.95398 Aug 23 499301.9 1663.29495 25890.08889 Sep 23 497560.7 -527.33854 25414.33728 Oct 23 503029.6 3330.79410 15555.41524 Nov 23 517262.7 10346.09429 -8023.68984 Dec 23 518340.8 4381.96765 -6102.82687 Jan 24 514137.9 -1142.52059 5026.08357 Feb 24 512120.8 -1705.28518 4888.21992 Mar 24 512514.3 -355.01844 -2581.25306 Apr 24 522293.2 6164.60303 -13166.18133 May 24 529489.5 6828.39224 -28632.49403 Jun 24 540864.3 9753.71717 -33893.29573 Jul 24 549929.6 9310.75875 19393.42042 Aug 24 554113.3 6012.19779 25600.72453 Sep 24 556490.2 3673.64179 21501.83103 Oct 24 555188.2 472.96032 10275.81899 Nov 24 552389.9 -1631.49313 -5045.85937 Dec 24 555753.5 1582.16676 -965.50820 Jan 25 557016.9 1377.07563 5308.11078 Feb 25 557208.5 614.50526 3645.46008 Mar 25 560587.5 2392.64655 -5255.47815 Apr 25 558968.5 -187.63955 -15369.50693 May 25 565139.3 3902.35085 -28477.28257 Jun 25 575135.5 7822.45451 -32413.53462 Jul 25 575107.1 2772.12598 18422.94260 Aug 25 581883.5 5347.78551 28879.49179 Sep 25 588827.0 6374.06580 23786.01272 Oct 25 598959.7 8791.37339 12364.34274 Nov 25 602666.4 5521.04071 -8499.35505 Dec 25 598664.9 -603.97971 -3210.87322 Jan 26 587748.4 -7237.04354 3116.56029 Feb 26 584548.4 -4640.62836 4830.60553 Mar 26 586783.6 -218.80359 -2355.60663 Apr 26 590429.6 2266.55120 -17329.56884 May 26 596604.4 4780.00878 -29148.39046 Jun 26 599440.9 3530.06465 -30412.92602 Jul 26 603566.7 3913.19594 17168.29419 Aug 26 602777.9 889.36075 26106.10476 Sep 26 605448.3 2034.66789 22783.66053 Oct 26 600206.5 -2644.33742 11910.54625 Nov 26 598872.1 -1801.94154 -3468.10698 Dec 26 596643.4 -2076.40983 497.63093 > m$resid Jan Feb Mar Apr May 1 0.0000000000 -1.9926245489 -0.2221448363 0.8355541311 0.4953143079 2 0.1417645788 -0.0696830154 -0.7953935380 -0.0755020089 0.8806576241 3 0.6008049968 -0.2995712971 -1.0794147995 -0.7153370136 0.7806513616 4 -0.4627731181 -0.5199203528 -0.6922547848 0.0093349620 0.7252389265 5 -0.0178243934 -0.1960992103 -0.1194990951 0.0406428229 1.8000311484 6 0.8669350029 -1.4798426987 -1.4375208003 0.0790367384 1.1296259181 7 -2.0895456708 -0.7120582856 0.3723211742 0.7596686716 1.0068162895 8 -1.6422258268 -1.2680019327 0.3701537681 0.9466119739 0.8759331563 9 -1.2925356924 -0.0748202172 -0.1992353460 0.4832226720 1.0061919016 10 -1.0463540070 -0.3509956883 0.8437646717 -0.2832904002 0.8419187693 11 -0.4920118053 -0.3170657762 -0.4971402650 1.1659557343 0.8606126899 12 -0.7608854790 0.1432260532 -0.4021206065 0.4832807924 0.7670219611 13 -0.4448250567 -0.8349801744 0.4184820068 0.7992576439 0.4618829379 14 -0.6180247221 -0.0883237321 -0.2804575538 0.1640280183 0.8958060495 15 -0.3178087483 -0.3999674556 -0.0973545160 0.2218973859 0.7088204778 16 -0.0378080231 0.0527596861 -0.1730225258 0.4570317940 0.3091416622 17 0.0554426548 -0.9491209611 -0.3088206987 0.4368904822 0.3138631634 18 -0.7739021538 0.6216919091 0.7137357127 -0.1492888489 0.1259876158 19 -0.3701020227 0.3742355547 0.2333005217 0.0045874856 0.6881973362 20 0.6973044862 -0.2383802967 0.1982177989 0.1872837030 0.7027549090 21 0.1371499174 0.2264561452 -0.2814408983 1.3323637687 0.2924492884 22 0.4982919734 0.6295713812 0.6548471932 0.1542950843 0.8072627342 23 0.0908424152 1.0805473287 1.2386392316 -0.2567227313 0.0319194555 24 -0.9966449775 -0.1015205268 0.2435916129 1.1762548136 0.1197649452 25 -0.0369995583 -0.1375659201 0.3207825327 -0.4655259734 0.7379319844 26 -1.1966438009 0.4683908820 0.7977144692 0.4483961234 0.4534827720 Jun Jul Aug Sep Oct 1 0.3457585999 6.1562470615 0.7064899597 -3.0216668326 -3.0029378233 2 2.1551562077 2.7059050518 0.6014487038 -2.0635922977 -2.6289167902 3 2.1671333440 2.4088089909 0.7019498766 -1.1871714255 -1.6456379840 4 2.0453105193 1.7789892175 1.3874581675 -0.5489519440 -1.8715891821 5 1.5247794305 1.9032097266 1.7457626323 -1.2815627410 -1.9358207387 6 1.2508854859 1.7318190998 0.6583419260 0.8507220775 -0.7504415246 7 2.1817474773 -0.0002106363 -0.3793785477 0.5856706699 1.3302801318 8 1.1213825981 1.0946990077 -0.2615007123 0.0528564310 -0.7304727634 9 1.2048537724 1.1957385700 0.4037236563 -1.0446664822 -0.8681253123 10 1.1361314099 0.5352086029 1.1446538134 -0.8113832692 -0.8000937114 11 1.0434200481 0.9732577676 -0.3339700796 0.3271178327 -0.3475553563 12 0.8257062708 0.4444776578 0.7663719371 -0.1788147232 -0.2740582882 13 0.8801367805 0.4685541469 0.3369413709 0.0468764873 -0.6839127289 14 0.5923443230 0.8357697409 0.3671279230 0.0290529312 -1.2940943227 15 0.6635623157 0.1688638835 0.9348614752 -0.1873572515 -0.5846102964 16 0.7268620363 1.1690448699 0.4823765712 -0.0837506620 -0.3662164840 17 0.2053732403 1.4732791733 0.9710261256 -0.6951613171 -1.5003130080 18 1.5170316307 -0.1987733614 -0.2932234493 0.0766989289 -0.9467808319 19 -0.0643262233 0.6495652882 1.3494019495 -1.0443017428 -1.7123579000 20 0.5775826357 0.3138100055 -0.0838887928 -0.9715366350 -0.0727659042 21 0.4440762967 0.2816479432 0.2396553681 -0.5150292305 -0.3751732050 22 -0.0667882490 0.2690597325 -0.7085550946 1.6576372546 -0.2173840746 23 0.6780117720 0.8183970744 -1.7688022576 -0.3951951251 0.6960778888 24 0.5277866269 -0.0799120033 -0.5950501729 -0.4218823995 -0.5774574002 25 0.7072589154 -0.9111079462 0.4646448368 0.1851446677 0.4361206270 26 -0.2255113933 0.0691192168 -0.5454989630 0.2066182104 -0.8441620539 Nov Dec 1 -1.1325818916 0.6210092763 2 -1.0473200294 0.1474594753 3 -1.0239460669 -0.6238265905 4 -2.6760259407 -1.4767119817 5 -1.2257091795 -1.8799961612 6 -1.6759538230 0.3214725437 7 -1.6677725275 -1.1974297395 8 0.0674519363 -1.6352065493 9 -0.0619834290 -0.6648499441 10 -0.5482540788 -0.6250864319 11 -0.8000618866 -0.6630874285 12 -0.9102807123 -0.7728042638 13 -0.3392090478 -0.1613912441 14 -0.7217841673 -1.0042997657 15 -1.4553206851 -0.4863572552 16 -1.5281818492 -0.6818688364 17 0.1209874718 -0.4080416849 18 -0.9042769855 -0.1058276452 19 -0.7212015808 0.1828501698 20 -0.6819226398 -0.7246721552 21 -0.9714955825 -0.9609770808 22 -2.7103858410 -0.6933628338 23 1.2657524870 -1.0760512835 24 -0.3796959902 0.5798056268 25 -0.5900427627 -1.1050625782 26 0.1519858943 -0.0495186398 > 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/wessaorg/rcomp/tmp/10szj1322560172.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/2zih41322560172.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/30j1d1322560172.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/48cbx1322560172.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/54np81322560172.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > hist(m$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/66xox1322560173.tab") > > try(system("convert tmp/10szj1322560172.ps tmp/10szj1322560172.png",intern=TRUE)) character(0) > try(system("convert tmp/2zih41322560172.ps tmp/2zih41322560172.png",intern=TRUE)) character(0) > try(system("convert tmp/30j1d1322560172.ps tmp/30j1d1322560172.png",intern=TRUE)) character(0) > try(system("convert tmp/48cbx1322560172.ps tmp/48cbx1322560172.png",intern=TRUE)) character(0) > try(system("convert tmp/54np81322560172.ps tmp/54np81322560172.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.278 0.262 5.554