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(8.64 + ,8.89 + ,8.87 + ,8.81 + ,8.87 + ,9.06 + ,9.12 + ,8.66 + ,8.17 + ,8.04 + ,7.71 + ,7.55 + ,7.52 + ,7.38 + ,7.52 + ,7.31 + ,6.92 + ,7.09 + ,7.05 + ,7.37 + ,7.05 + ,6.79 + ,6.35 + ,6.44 + ,6.89 + ,7.16 + ,7.46 + ,7.91 + ,7.86 + ,8.02 + ,8.38 + ,8.50 + ,8.40 + ,8.24 + ,8.33 + ,8.28 + ,8.15 + ,8.06 + ,7.79 + ,7.28 + ,7.52 + ,7.23 + ,7.13 + ,7.21 + ,6.99 + ,6.77 + ,6.69 + ,6.39 + ,6.85 + ,6.74 + ,6.56 + ,6.62 + ,6.71 + ,6.67 + ,6.54 + ,6.14 + ,6.13 + ,5.86 + ,5.88 + ,5.75 + ,5.53 + ,5.86 + ,5.90 + ,5.95 + ,5.69 + ,5.53 + ,5.71 + ,5.60 + ,5.73 + ,5.60 + ,5.41 + ,5.13 + ,5.00 + ,5.04 + ,5.10 + ,4.96 + ,4.90 + ,4.80 + ,4.48 + ,4.29 + ,4.27 + ,4.18 + ,4.02 + ,3.82 + ,4.13 + ,4.16 + ,3.98 + ,4.26 + ,4.70 + ,4.96 + ,5.13 + ,5.35 + ,5.41 + ,5.42 + ,5.51 + ,5.75 + ,5.67 + ,5.46 + ,5.56 + ,5.56 + ,5.54 + ,5.53 + ,5.65 + ,5.58 + ,5.57 + ,5.36 + ,5.23 + ,5.11 + ,5.07 + ,5.04 + ,5.34 + ,5.43 + ,5.31 + ,5.12 + ,4.97 + ,5.00 + ,4.64 + ,4.80 + ,5.10 + ,5.11 + ,5.12 + ,5.36 + ,5.26 + ,5.27 + ,5.10 + ,4.94 + ,4.68 + ,4.41 + ,4.60 + ,4.53 + ,4.18 + ,4.00 + ,3.87 + ,4.09 + ,4.13 + ,3.74 + ,3.81 + ,4.11 + ,4.14 + ,3.99 + ,4.28 + ,4.37 + ,4.24 + ,4.19 + ,4.01 + ,3.95 + ,4.30 + ,4.37 + ,4.40 + ,4.29 + ,4.12 + ,4.07 + ,3.93 + ,3.79 + ,3.67 + ,3.53 + ,3.69 + ,3.69 + ,3.48 + ,3.31 + ,3.16 + ,3.25 + ,3.14 + ,3.19 + ,3.43 + ,3.45 + ,3.31 + ,3.51 + ,3.53 + ,3.83 + ,4.02 + ,3.99 + ,4.11 + ,3.96 + ,3.83 + ,3.71 + ,3.81 + ,3.73 + ,3.99 + ,4.17 + ,4.00 + ,4.10 + ,4.24 + ,4.45 + ,4.62 + ,4.49 + ,4.45 + ,4.49 + ,4.36 + ,4.32 + ,4.45 + ,4.13 + ,4.14 + ,4.30 + ,4.42 + ,4.67 + ,4.96 + ,4.73 + ,4.52 + ,4.36 + ,4.15 + ,3.92 + ,3.88 + ,4.20 + ,3.95 + ,3.78 + ,3.69 + ,3.77 + ,3.66 + ,3.53 + ,3.50 + ,3.14 + ,3.42 + ,3.30 + ,2.81 + ,3.15 + ,3.37 + ,4.05 + ,4.00 + ,4.20 + ,4.21 + ,4.24 + ,4.24 + ,4.17 + ,4.12 + ,4.35 + ,3.98 + ,3.62 + ,4.39 + ,5.01 + ,4.07 + ,3.70 + ,3.59 + ,3.44 + ,3.33 + ,2.98 + ,3.14 + ,2.55 + ,2.49 + ,2.53 + ,2.43) > par1 = '12' > 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 0.0503465 0.0000000 0.0000000 0.0000000 > m$fitted level slope sea Jan 1 8.640000 0.000000e+00 0.000000e+00 Feb 1 8.877000 1.300000e-02 1.300000e-02 Mar 1 8.857131 1.286853e-02 1.286853e-02 Apr 1 8.797421 1.257936e-02 1.257936e-02 May 1 8.857233 1.276680e-02 1.276680e-02 Jun 1 9.046535 1.346457e-02 1.346457e-02 Jul 1 9.106353 1.364706e-02 1.364706e-02 Aug 1 8.648203 1.179687e-02 1.179687e-02 Sep 1 8.160156 9.844358e-03 9.844358e-03 Oct 1 8.030698 9.302325e-03 9.302325e-03 Nov 1 7.702008 7.992278e-03 7.992278e-03 Dec 1 7.542654 7.346154e-03 7.346154e-03 Jan 2 7.584672 5.879265e-03 -6.467191e-02 Feb 2 7.379236 7.636361e-04 7.636380e-04 Mar 2 7.518984 1.016334e-03 1.016334e-03 Apr 2 7.309366 6.340578e-04 6.340578e-04 May 2 6.920072 -7.233296e-05 -7.233296e-05 Jun 2 7.089765 2.346568e-04 2.346568e-04 Jul 2 7.049838 1.621619e-04 1.621619e-04 Aug 2 7.369263 7.374099e-04 7.374099e-04 Sep 2 7.049838 1.615797e-04 1.615797e-04 Oct 2 6.790305 -3.046597e-04 -3.046597e-04 Nov 2 6.351091 -1.091235e-03 -1.091235e-03 Dec 2 6.440929 -9.285717e-04 -9.285717e-04 Jan 3 6.801645 -8.032306e-03 8.835536e-02 Feb 3 7.162306 -2.305883e-03 -2.305880e-03 Mar 3 7.461951 -1.950647e-03 -1.950647e-03 Apr 3 7.911420 -1.420188e-03 -1.420188e-03 May 3 7.861477 -1.477140e-03 -1.477140e-03 Jun 3 8.021288 -1.288056e-03 -1.288056e-03 Jul 3 8.380865 -8.654972e-04 -8.654972e-04 Aug 3 8.500724 -7.242992e-04 -7.242992e-04 Sep 3 8.400840 -8.401402e-04 -8.401402e-04 Oct 3 8.241026 -1.025641e-03 -1.025641e-03 Nov 3 8.330920 -9.196742e-04 -9.196742e-04 Dec 3 8.280977 -9.767444e-04 -9.767444e-04 Jan 4 8.156616 6.014270e-04 -6.615698e-03 Feb 4 8.060504 -5.043480e-04 -5.043467e-04 Mar 4 7.790738 -7.384885e-04 -7.384885e-04 Apr 4 7.281181 -1.180556e-03 -1.180556e-03 May 4 7.520971 -9.713793e-04 -9.713793e-04 Jun 4 7.231222 -1.221837e-03 -1.221837e-03 Jul 4 7.131307 -1.307360e-03 -1.307360e-03 Aug 4 7.211237 -1.237025e-03 -1.237025e-03 Sep 4 6.991426 -1.426102e-03 -1.426102e-03 Oct 4 6.771615 -1.614854e-03 -1.614854e-03 Nov 4 6.691682 -1.682485e-03 -1.682485e-03 Dec 4 6.391940 -1.939656e-03 -1.939656e-03 Jan 5 6.787229 -5.706480e-03 6.277127e-02 Feb 5 6.746028 -6.027587e-03 -6.027583e-03 Mar 5 6.566147 -6.147485e-03 -6.147485e-03 Apr 5 6.626102 -6.101929e-03 -6.101929e-03 May 5 6.716036 -6.035789e-03 -6.035789e-03 Jun 5 6.676059 -6.059148e-03 -6.059148e-03 Jul 5 6.546144 -6.144330e-03 -6.144330e-03 Aug 5 6.146415 -6.414836e-03 -6.414836e-03 Sep 5 6.136417 -6.417296e-03 -6.417296e-03 Oct 5 5.866598 -6.598080e-03 -6.598080e-03 Nov 5 5.886580 -6.579850e-03 -6.579850e-03 Dec 5 5.756664 -6.664384e-03 -6.664384e-03 Jan 6 5.479140 -4.623656e-03 5.086022e-02 Feb 6 5.861726 -1.725715e-03 -1.725711e-03 Mar 6 5.901702 -1.701885e-03 -1.701885e-03 Apr 6 5.951672 -1.672375e-03 -1.672375e-03 May 6 5.691820 -1.819738e-03 -1.819738e-03 Jun 6 5.531910 -1.909921e-03 -1.909921e-03 Jul 6 5.711806 -1.806268e-03 -1.806268e-03 Aug 6 5.601868 -1.867882e-03 -1.867882e-03 Sep 6 5.731793 -1.792829e-03 -1.792829e-03 Oct 6 5.601866 -1.865757e-03 -1.865757e-03 Nov 6 5.411973 -1.972712e-03 -1.972712e-03 Dec 6 5.132131 -2.130682e-03 -2.130682e-03 Jan 7 4.986433 -1.233387e-03 1.356725e-02 Feb 7 5.040878 -8.780493e-04 -8.780453e-04 Mar 7 5.100848 -8.483672e-04 -8.483672e-04 Apr 7 4.960916 -9.161798e-04 -9.161798e-04 May 7 4.900945 -9.449591e-04 -9.449591e-04 Jun 7 4.800993 -9.931846e-04 -9.931846e-04 Jul 7 4.481148 -1.148419e-03 -1.148419e-03 Aug 7 4.291240 -1.240273e-03 -1.240273e-03 Sep 7 4.271249 -1.249393e-03 -1.249393e-03 Oct 7 4.181293 -1.292518e-03 -1.292518e-03 Nov 7 4.021370 -1.369597e-03 -1.369597e-03 Dec 7 3.821466 -1.466020e-03 -1.466020e-03 Jan 8 4.097570 -2.948190e-03 3.243008e-02 Feb 8 4.162570 -2.570213e-03 -2.570209e-03 Mar 8 3.982646 -2.645683e-03 -2.645683e-03 Apr 8 4.262526 -2.525511e-03 -2.525511e-03 May 8 4.702337 -2.337442e-03 -2.337442e-03 Jun 8 4.962226 -2.225999e-03 -2.225999e-03 Jul 8 5.132153 -2.152867e-03 -2.152867e-03 Aug 8 5.352059 -2.058574e-03 -2.058574e-03 Sep 8 5.412032 -2.032245e-03 -2.032245e-03 Oct 8 5.422027 -2.027142e-03 -2.027142e-03 Nov 8 5.511988 -1.988131e-03 -1.988131e-03 Dec 8 5.751886 -1.885594e-03 -1.885594e-03 Jan 9 5.654172 -1.438936e-03 1.582830e-02 Feb 9 5.462377 -2.377359e-03 -2.377355e-03 Mar 9 5.562339 -2.338741e-03 -2.338741e-03 Apr 9 5.562338 -2.337859e-03 -2.337859e-03 May 9 5.542345 -2.344516e-03 -2.344516e-03 Jun 9 5.532347 -2.347401e-03 -2.347401e-03 Jul 9 5.652301 -2.301319e-03 -2.301319e-03 Aug 9 5.582327 -2.326808e-03 -2.326808e-03 Sep 9 5.572330 -2.329696e-03 -2.329696e-03 Oct 9 5.362408 -2.407826e-03 -2.407826e-03 Nov 9 5.232456 -2.455811e-03 -2.455811e-03 Dec 9 5.112500 -2.500001e-03 -2.500001e-03 Jan 10 5.045437 -2.233010e-03 2.456311e-02 Feb 10 5.042237 -2.237289e-03 -2.237285e-03 Mar 10 5.342135 -2.134870e-03 -2.134870e-03 Apr 10 5.432104 -2.103659e-03 -2.103659e-03 May 10 5.312144 -2.143583e-03 -2.143583e-03 Jun 10 5.122207 -2.207177e-03 -2.207177e-03 Jul 10 4.972257 -2.257192e-03 -2.257192e-03 Aug 10 5.002246 -2.246279e-03 -2.246279e-03 Sep 10 4.642367 -2.367265e-03 -2.367265e-03 Oct 10 4.802312 -2.312374e-03 -2.312374e-03 Nov 10 5.102210 -2.210207e-03 -2.210207e-03 Dec 10 5.112206 -2.206081e-03 -2.206081e-03 Jan 11 5.096293 -2.155145e-03 2.370659e-02 Feb 11 5.361083 -1.083077e-03 -1.083074e-03 Mar 11 5.261114 -1.113504e-03 -1.113504e-03 Apr 11 5.271110 -1.110087e-03 -1.110087e-03 May 11 5.101162 -1.162005e-03 -1.162005e-03 Jun 11 4.941211 -1.210818e-03 -1.210818e-03 Jul 11 4.681290 -1.290323e-03 -1.290323e-03 Aug 11 4.411373 -1.372851e-03 -1.372851e-03 Sep 11 4.601314 -1.314093e-03 -1.314093e-03 Oct 11 4.531335 -1.335175e-03 -1.335175e-03 Nov 11 4.181442 -1.442161e-03 -1.442161e-03 Dec 11 4.001497 -1.496933e-03 -1.496933e-03 Jan 12 3.858776 -1.020409e-03 1.122449e-02 Feb 12 4.090166 -1.661977e-04 -1.661936e-04 Mar 12 4.130155 -1.548865e-04 -1.548865e-04 Apr 12 3.740265 -2.646402e-04 -2.646402e-04 May 12 3.810245 -2.448640e-04 -2.448640e-04 Jun 12 4.110160 -1.603832e-04 -1.603832e-04 Jul 12 4.140152 -1.518993e-04 -1.518993e-04 Aug 12 3.990194 -1.940388e-04 -1.940388e-04 Sep 12 4.280112 -1.124548e-04 -1.124548e-04 Oct 12 4.370087 -8.712811e-05 -8.712811e-05 Nov 12 4.240124 -1.236307e-04 -1.236307e-04 Dec 12 4.190138 -1.376410e-04 -1.376410e-04 Jan 13 4.014453 4.047808e-04 -4.452593e-03 Feb 13 3.949816 1.844151e-04 1.844189e-04 Mar 13 4.299725 2.752528e-04 2.752528e-04 Apr 13 4.369707 2.933538e-04 2.933538e-04 May 13 4.399699 3.010638e-04 3.010638e-04 Jun 13 4.289728 2.724439e-04 2.724439e-04 Jul 13 4.119772 2.282746e-04 2.282746e-04 Aug 13 4.069785 2.152486e-04 2.152486e-04 Sep 13 3.929821 1.788952e-04 1.788952e-04 Oct 13 3.789857 1.425606e-04 1.425606e-04 Nov 13 3.669889 1.114275e-04 1.114275e-04 Dec 13 3.529925 7.512916e-05 7.512916e-05 Jan 14 3.685938 -3.692543e-04 4.061795e-03 Feb 14 3.690354 -3.542173e-04 -3.542141e-04 Mar 14 3.480405 -4.047222e-04 -4.047222e-04 Apr 14 3.310446 -4.455689e-04 -4.455689e-04 May 14 3.160482 -4.815801e-04 -4.815801e-04 Jun 14 3.250460 -4.597983e-04 -4.597983e-04 Jul 14 3.140486 -4.861617e-04 -4.861617e-04 Aug 14 3.190474 -4.740140e-04 -4.740140e-04 Sep 14 3.430416 -4.161660e-04 -4.161660e-04 Oct 14 3.450411 -4.112559e-04 -4.112559e-04 Nov 14 3.310445 -4.448190e-04 -4.448190e-04 Dec 14 3.510397 -3.966351e-04 -3.966351e-04 Jan 15 3.525195 -4.368143e-04 4.804954e-03 Feb 15 3.829544 4.561793e-04 4.561833e-04 Mar 15 4.019501 4.987639e-04 4.987639e-04 Apr 15 3.989508 4.919133e-04 4.919133e-04 May 15 4.109481 5.187510e-04 5.187510e-04 Jun 15 3.959515 4.849569e-04 4.849569e-04 Jul 15 3.829544 4.556673e-04 4.556673e-04 Aug 15 3.709571 4.286351e-04 4.286351e-04 Sep 15 3.809549 4.509755e-04 4.509755e-04 Oct 15 3.729567 4.329291e-04 4.329291e-04 Nov 15 3.989509 4.911411e-04 4.911411e-04 Dec 15 4.169469 5.313897e-04 5.313897e-04 Jan 16 4.010181 9.255617e-04 -1.018118e-02 Feb 16 4.098834 1.166315e-03 1.166319e-03 Mar 16 4.238804 1.195537e-03 1.195537e-03 Apr 16 4.448761 1.239478e-03 1.239478e-03 May 16 4.618725 1.274984e-03 1.274984e-03 Jun 16 4.488753 1.247370e-03 1.247370e-03 Jul 16 4.448761 1.238696e-03 1.238696e-03 Aug 16 4.488753 1.246846e-03 1.246846e-03 Sep 16 4.358781 1.219255e-03 1.219255e-03 Oct 16 4.318789 1.210592e-03 1.210592e-03 Nov 16 4.448762 1.237655e-03 1.237655e-03 Dec 16 4.128830 1.170168e-03 1.170168e-03 Jan 17 4.152305 1.118623e-03 -1.230485e-02 Feb 17 4.298507 1.493069e-03 1.493072e-03 Mar 17 4.418483 1.516531e-03 1.516531e-03 Apr 17 4.668434 1.565716e-03 1.565716e-03 May 17 4.958377 1.622798e-03 1.622798e-03 Jun 17 4.728423 1.576968e-03 1.576968e-03 Jul 17 4.518465 1.535113e-03 1.535113e-03 Aug 17 4.358497 1.503164e-03 1.503164e-03 Sep 17 4.148539 1.461340e-03 1.461340e-03 Oct 17 3.918584 1.415579e-03 1.415579e-03 Nov 17 3.878593 1.407392e-03 1.407392e-03 Dec 17 4.198530 1.470355e-03 1.470355e-03 Jan 18 3.971635 1.966801e-03 -2.163482e-02 Feb 18 3.778508 1.491588e-03 1.491591e-03 Mar 18 3.688526 1.474490e-03 1.474490e-03 Apr 18 3.768511 1.489163e-03 1.489163e-03 May 18 3.658532 1.468335e-03 1.468335e-03 Jun 18 3.528556 1.443780e-03 1.443780e-03 Jul 18 3.498562 1.437908e-03 1.437908e-03 Aug 18 3.138630 1.370425e-03 1.370425e-03 Sep 18 3.418578 1.422438e-03 1.422438e-03 Oct 18 3.298600 1.399776e-03 1.399776e-03 Nov 18 2.808692 1.308079e-03 1.308079e-03 Dec 18 3.148629 1.371268e-03 1.371268e-03 Jan 19 3.379894 8.994705e-04 -9.894179e-03 Feb 19 4.047563 2.437168e-03 2.437171e-03 Mar 19 3.997572 2.427888e-03 2.427888e-03 Apr 19 4.197537 2.462845e-03 2.462845e-03 May 19 4.207536 2.464178e-03 2.464178e-03 Jun 19 4.237531 2.469048e-03 2.469048e-03 Jul 19 4.237531 2.468611e-03 2.468611e-03 Aug 19 4.167544 2.455799e-03 2.455799e-03 Sep 19 4.117553 2.446526e-03 2.446526e-03 Oct 19 4.347513 2.486744e-03 2.486744e-03 Nov 19 3.977579 2.420922e-03 2.420922e-03 Dec 19 3.617643 2.356890e-03 2.356890e-03 Jan 20 4.399267 8.424142e-04 -9.266561e-03 Feb 20 5.007827 2.173109e-03 2.173114e-03 Mar 20 4.067985 2.014786e-03 2.014786e-03 Apr 20 3.698048 1.952284e-03 1.952284e-03 May 20 3.588067 1.933478e-03 1.933478e-03 Jun 20 3.438092 1.907960e-03 1.907960e-03 Jul 20 3.328111 1.889168e-03 1.889168e-03 Aug 20 2.978170 1.830086e-03 1.830086e-03 Sep 20 3.138143 1.856638e-03 1.856638e-03 Oct 20 2.548243 1.757300e-03 1.757300e-03 Nov 20 2.488253 1.746936e-03 1.746936e-03 Dec 20 2.528247 1.753355e-03 1.753355e-03 Jan 21 2.450893 1.899358e-03 -2.089294e-02 > m$resid Jan Feb Mar Apr May Jun 1 0.00000000 0.63420237 -0.14677849 -0.32410962 0.21092241 0.78832233 2 0.18705485 -0.80281382 0.61997413 -0.93958847 -1.73937179 0.75728036 3 1.77736620 1.49361422 1.34650084 2.01303506 -0.21637967 0.71923692 4 -0.58730072 -0.40264486 -1.20054477 -2.26865063 1.07440797 -1.28756138 5 1.86037957 -0.15003072 -0.77507908 0.29469928 0.42815197 -0.15131692 6 -1.25617479 1.65251946 0.18590673 0.23035505 -1.15096545 -0.70476414 7 -0.66146794 0.23921291 0.27125028 -0.62000873 -0.26325590 -0.44135310 8 1.27286389 0.29335813 -0.79058665 1.25940484 1.97179314 1.16891615 9 -0.43789148 -0.82491037 0.45618117 0.01042115 -0.07870038 -0.03411192 10 -0.29421137 -0.00420115 1.34675872 0.41054976 -0.52534200 -0.83708172 11 -0.06232248 1.16300519 -0.44077720 0.04952216 -0.75257934 -0.70778768 12 -0.64097213 1.01455104 0.17898431 -1.73718590 0.31310575 1.33791900 13 -0.79555035 -0.28439982 1.55882767 0.31070333 0.13237702 -0.49151717 14 0.70578157 0.02095346 -0.93421997 -0.75574763 -0.66644196 0.40320252 15 0.06869788 1.33620458 0.84464884 -0.13590918 0.53255426 -0.67074461 16 -0.72186498 0.38500988 0.61867774 0.93048509 0.75203926 -0.58499430 17 0.10066203 0.63732560 0.52809993 1.10731162 1.28534362 -1.03217581 18 -1.02985663 -0.85771693 -0.40771427 0.34993351 -0.49682956 -0.58586283 19 1.03607412 2.93357334 -0.23367708 0.88044567 0.03358802 0.12270859 20 3.50989927 2.67553292 -4.19864883 -1.65782643 -0.49889807 -0.67706809 21 -0.35611884 Jul Aug Sep Oct Nov Dec 1 0.20698834 -2.10678538 -2.23201298 -0.62203812 -1.50925336 -0.74725335 2 -0.17915298 1.42414523 -1.42815308 -1.15842788 -1.95784543 0.40560549 3 1.60921779 0.53834894 -0.44218578 -0.70891744 0.40543959 -0.21861006 4 -0.44003599 0.36220736 -0.97454389 -0.97370195 -0.34918990 -1.32894442 5 -0.55217982 -1.75470153 -0.01597259 -1.17431137 0.11849956 -0.54986064 6 0.81049056 -0.48205184 0.58753095 -0.57122092 -0.83822326 -1.23873769 7 -1.42137807 -0.84145390 -0.08358652 -0.39544049 -0.70714302 -0.88502518 8 0.76740006 0.98986297 0.27651901 0.05361297 0.41005226 1.07824481 9 0.54516540 -0.30165726 -0.03419083 -0.92535427 -0.56853565 -0.52376305 10 -0.65855976 0.14373695 -1.59413852 0.72350310 1.34709390 0.05440828 11 -1.15317373 -1.19737986 0.85276426 -0.30606687 -1.55366305 -0.79566022 12 0.13439747 -0.66773711 1.29313175 0.40154953 -0.57890394 -0.22225379 13 -0.75875816 -0.22382432 -0.62481908 -0.62465710 -0.53537236 -0.62435650 14 -0.48813125 0.22497561 1.07159642 0.09097819 -0.62203314 0.89321904 15 -0.58146964 -0.53677693 0.44371190 -0.35850725 1.15668801 0.79993102 16 -0.18380865 0.17273012 -0.58486895 -0.18368337 0.57391801 -1.43151587 17 -0.94284602 -0.71984556 -0.94251717 -1.03145639 -0.18455939 1.41973771 18 -0.14012304 -1.61067715 1.24165807 -0.54109530 -2.18982683 1.50931422 19 -0.01100288 -0.32294375 -0.23376014 1.01405248 -1.65992242 -1.61506585 20 -0.49870056 -1.56813981 0.70485984 -2.63751791 -0.27521189 0.17046889 21 > 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/10ybu1353595171.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/27btd1353595171.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/394801353595171.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/4zo0l1353595171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(as.numeric(m$resid),main='Standardized Residuals',ylab='Residuals',xlab='time',type='b') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5a2uj1353595171.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > hist(m$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/6t95l1353595171.tab") > > try(system("convert tmp/10ybu1353595171.ps tmp/10ybu1353595171.png",intern=TRUE)) character(0) > try(system("convert tmp/27btd1353595171.ps tmp/27btd1353595171.png",intern=TRUE)) character(0) > try(system("convert tmp/394801353595171.ps tmp/394801353595171.png",intern=TRUE)) character(0) > try(system("convert tmp/4zo0l1353595171.ps tmp/4zo0l1353595171.png",intern=TRUE)) character(0) > try(system("convert tmp/5a2uj1353595171.ps tmp/5a2uj1353595171.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.724 0.659 6.366