R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(-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) > par8 = 'FALSE' > par7 = '1' > par6 = '' > par5 = '1' > par4 = '' > par3 = '0' > par2 = 'periodic' > par1 = '12' > main = 'Seasonal Decomposition by Loess' > #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) #seasonal period > if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window > par3 <- as.numeric(par3) #s.degree > if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window > par5 <- as.numeric(par5)#t.degree > if (par6 != '') par6 <- as.numeric(par6)#l.window > par7 <- as.numeric(par7)#l.degree > if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust > nx <- length(x) > x <- ts(x,frequency=par1) > if (par6 != '') { + m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8) + } else { + m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8) + } > m$time.series seasonal trend remainder Jan 1 -8.707364 -6.43763082 -30.45500549 Feb 1 23.443477 -6.32480477 -1.01867255 Mar 1 40.084647 -6.21197872 -9.97266827 Apr 1 21.697368 -6.35398509 23.95661667 May 1 -71.570551 -6.49599147 38.66654246 Jun 1 23.909090 -6.75996888 -17.44912100 Jul 1 32.266105 -7.02394630 -7.94215867 Aug 1 18.176210 -7.55265279 7.07644293 Sep 1 16.460484 -8.08135929 23.02087573 Oct 1 -21.035664 -10.08958890 2.52525316 Nov 1 -1.415686 -12.09781852 -3.68649550 Dec 1 -73.308116 -13.71560638 8.02372260 Jan 2 -8.707364 -15.33339424 -23.85924207 Feb 2 23.443477 -15.62733844 1.28386113 Mar 2 40.084647 -15.92128264 -13.56336434 Apr 2 21.697368 -15.12038955 -30.47697887 May 2 -71.570551 -14.31949646 40.89004745 Jun 2 23.909090 -12.56021331 -53.54887657 Jul 2 32.266105 -10.80093017 21.73482519 Aug 2 18.176210 -7.85466000 21.77845014 Sep 2 16.460484 -4.90838984 -26.85209372 Oct 2 -21.035664 -1.24127694 44.07694120 Nov 2 -1.415686 2.42583595 -13.01014997 Dec 2 -73.308116 5.46374847 -27.95563225 Jan 3 -8.707364 8.50166099 -14.09429729 Feb 3 23.443477 10.20559449 14.15092820 Mar 3 40.084647 11.90952799 12.80582503 Apr 3 21.697368 12.89925009 5.60338149 May 3 -71.570551 13.88897219 28.88157880 Jun 3 23.909090 14.93569601 -15.34478589 Jul 3 32.266105 15.98241983 22.05147520 Aug 3 18.176210 15.55333321 -21.42954307 Sep 3 16.460484 15.12424658 11.91526986 Oct 3 -21.035664 13.65934962 -22.72368536 Nov 3 -1.415686 12.19445265 -16.07876667 Dec 3 -73.308116 10.48711091 38.82100531 Jan 4 -8.707364 8.77976918 11.02759452 Feb 4 23.443477 6.99743879 -8.94091610 Mar 4 40.084647 5.21510841 -6.79975539 Apr 4 21.697368 3.99908429 -8.89645270 May 4 -71.570551 2.78306017 32.58749082 Jun 4 23.909090 2.30158520 -20.21067508 Jul 4 32.266105 1.82011022 -7.48621519 Aug 4 18.176210 1.46855713 -27.64476699 Sep 4 16.460484 1.11700404 -4.37748759 Oct 4 -21.035664 1.03498719 -3.59932293 Nov 4 -1.415686 0.95297034 19.86271564 Dec 4 -73.308116 1.00388735 26.10422887 Jan 5 -8.707364 1.05480436 -0.54744067 Feb 5 23.443477 1.32406851 9.03245418 Mar 5 40.084647 1.59333265 -25.07797963 Apr 5 21.697368 1.41589910 -17.71326752 May 5 -71.570551 1.23846555 45.33208545 Jun 5 23.909090 1.37748359 -30.58657347 Jul 5 32.266105 1.51650163 -17.08260661 Aug 5 18.176210 1.70768886 -0.88389873 Sep 5 16.460484 1.89887609 6.44064035 Oct 5 -21.035664 2.36705822 7.26860603 Nov 5 -1.415686 2.83524035 3.48044563 Dec 5 -73.308116 2.84785463 11.76026159 Jan 6 -8.707364 2.86046891 22.64689478 Feb 6 23.443477 1.65929756 -11.50277488 Mar 6 40.084647 0.45812621 -34.14277320 Apr 6 21.697368 -2.55034219 3.65297377 May 6 -71.570551 -5.55881059 57.52936158 Jun 6 23.909090 -9.11710838 -12.59198151 Jul 6 32.266105 -12.67540616 0.20930119 Aug 6 18.176210 -15.41859947 -13.45761040 Sep 6 16.460484 -18.16179277 6.40130921 Oct 6 -21.035664 -18.67566252 -4.78867323 Nov 6 -1.415686 -19.18953226 -14.09478176 Dec 6 -73.308116 -18.33832891 -28.05355486 Jan 7 -8.707364 -17.48712556 -16.00551074 Feb 7 23.443477 -15.09312329 -13.75035402 Mar 7 40.084647 -12.69912102 -8.28552597 Apr 7 21.697368 -9.30181350 6.40444509 May 7 -71.570551 -5.90450599 75.17505698 Jun 7 23.909090 -2.09167420 -21.61741568 Jul 7 32.266105 1.72115758 -13.08726256 Aug 7 18.176210 3.67378275 -18.14999262 Sep 7 16.460484 5.62640792 28.31310852 Oct 7 -21.035664 6.44627633 -4.01061207 Nov 7 -1.415686 7.26614473 4.74954125 Dec 7 -73.308116 7.66623130 -0.35811507 Jan 8 -8.707364 8.06631787 10.64104583 Feb 8 23.443477 7.74566665 -3.98914396 Mar 8 40.084647 7.42501543 -34.00966241 Apr 8 21.697368 6.17667362 19.32595796 May 8 -71.570551 4.92833181 46.34221918 Jun 8 23.909090 4.33302144 -5.14211132 Jul 8 32.266105 3.73771107 -23.40381604 Aug 8 18.176210 2.72404790 -1.10025777 Sep 8 16.460484 1.71038474 -12.77086830 Oct 8 -21.035664 0.44408512 -4.60842087 Nov 8 -1.415686 -0.82221450 -4.26209952 Dec 8 -73.308116 -0.96088160 27.76899783 Jan 9 -8.707364 -1.09954871 7.20691241 Feb 9 23.443477 -0.36556029 -23.37791703 Mar 9 40.084647 0.36842814 -1.95307512 Apr 9 21.697368 0.14359497 -30.74096339 May 9 -71.570551 -0.08123819 33.65178918 Jun 9 23.909090 0.05564067 -4.46473056 Jul 9 32.266105 0.19251953 19.24137549 Aug 9 18.176210 0.67252919 0.55126094 Sep 9 16.460484 1.15253886 0.58697758 Oct 9 -21.035664 1.01151964 -30.77585539 Nov 9 -1.415686 0.87050043 -5.55481445 Dec 9 -73.308116 0.27972486 18.42839136 Jan 10 -8.707364 -0.31105070 21.11841440 Feb 10 23.443477 -1.01729145 3.87381414 Mar 10 40.084647 -1.72353220 -18.86111479 Apr 10 21.697368 -3.57818499 -18.91918342 May 10 -71.570551 -5.43283779 27.40338878 Jun 10 23.909090 -8.89760585 13.78851596 Jul 10 32.266105 -12.36237391 11.79626894 Aug 10 18.176210 -15.50373433 -0.37247554 Sep 10 16.460484 -18.64509475 5.98461119 Oct 10 -21.035664 -19.68083724 -25.48349851 Nov 10 -1.415686 -20.71657973 1.63226571 Dec 10 -73.308116 -19.89063969 -20.00124408 Jan 11 -8.707364 -19.06469966 -37.42793665 Feb 11 23.443477 -15.87763408 -11.46584324 Mar 11 40.084647 -12.69056850 -18.29407848 Apr 11 21.697368 -8.67248968 10.17512126 May 11 -71.570551 -4.65441085 37.12496184 Jun 11 23.909090 -0.81826053 -10.59082935 Jul 11 32.266105 3.01788979 13.81600524 Aug 11 18.176210 6.11003180 30.61375833 Sep 11 16.460484 9.20217382 5.13734263 Oct 11 -21.035664 10.47539853 7.06026572 Nov 11 -1.415686 11.74862325 -38.63293727 Dec 11 -73.308116 11.10910662 1.19900961 Jan 12 -8.707364 10.46958998 -3.76222629 Feb 12 23.443477 8.75338897 7.80313372 Mar 12 40.084647 7.03718796 26.87816506 Apr 12 21.697368 5.76173063 -4.35909905 May 12 -71.570551 4.48627330 21.78427769 Jun 12 23.909090 3.88158340 -10.29067328 Jul 12 32.266105 3.27689350 -9.74299847 Aug 12 18.176210 1.92179127 -4.89800113 Sep 12 16.460484 0.56668903 -20.62717259 Oct 12 -21.035664 -0.58435589 -18.87997985 Nov 12 -1.415686 -1.73540082 14.65108680 Dec 12 -73.308116 -1.82558420 15.33370043 Jan 13 -8.707364 -1.91576758 33.92313128 Feb 13 23.443477 -1.94073187 -49.30274545 Mar 13 40.084647 -1.96569615 17.58104916 Apr 13 21.697368 -3.67814547 4.68077705 May 13 -71.570551 -5.39059479 -2.23885422 Jun 13 23.909090 -7.90127302 12.79218314 Jul 13 32.266105 -10.41195126 -4.55415371 Aug 13 18.176210 -11.34316420 32.76695434 Sep 13 16.460484 -12.27437714 -26.38610641 Oct 13 -21.035664 -11.92780741 -10.03652834 Nov 13 -1.415686 -11.58123768 -37.30307635 Dec 13 -73.308116 -10.11942297 -3.07246080 Jan 14 -8.707364 -8.65760827 -14.53502804 Feb 14 23.443477 -5.98237639 5.63889908 Mar 14 40.084647 -3.30714452 16.82249754 Apr 14 21.697368 -0.11881535 0.02144694 May 14 -71.570551 3.06951381 4.30103718 Jun 14 23.909090 5.41144541 5.87946471 Jul 14 32.266105 7.75337700 12.08051803 Aug 14 18.176210 8.29182316 14.13196697 Sep 14 16.460484 8.83026932 -8.19075288 Oct 14 -21.035664 8.45232940 4.78333485 Nov 14 -1.415686 8.07438948 -16.65870350 Dec 14 -73.308116 7.32184908 7.98626714 Jan 15 -8.707364 6.56930869 16.13805501 Feb 15 23.443477 5.65466841 -13.29814573 Mar 15 40.084647 4.74002814 1.17532488 Apr 15 21.697368 3.53583729 -34.13320570 May 15 -71.570551 2.33164644 42.53890455 Jun 15 23.909090 1.01420607 14.07670405 Jul 15 32.266105 -0.30323431 -33.26287067 Aug 15 18.176210 -1.01993868 21.54372881 Sep 15 16.460484 -1.73664305 7.37615949 Oct 15 -21.035664 -1.95319663 -26.21113912 Nov 15 -1.415686 -2.16975022 0.18543620 Dec 15 -73.308116 -1.94929103 -11.44259275 Jan 16 -8.707364 -1.72883184 -13.86380446 Feb 16 23.443477 -1.02160236 20.37812505 Mar 16 40.084647 -0.31437288 5.12972589 Apr 16 21.697368 0.15419447 -17.45156289 May 16 -71.570551 0.62276183 10.44778917 Jun 16 23.909090 1.11585964 16.37505048 Jul 16 32.266105 1.60895745 4.62493758 Aug 16 18.176210 1.78597758 8.53781256 Sep 16 16.460484 1.96299770 -10.82348126 Oct 16 -21.035664 1.88598437 -27.25032011 Nov 16 -1.415686 1.80897103 6.60671495 Dec 16 -73.308116 1.90098055 -1.59286432 Jan 17 -8.707364 1.99299006 12.41437363 Feb 17 23.443477 2.40552440 -2.24900171 Mar 17 40.084647 2.81805873 -3.50270572 Apr 17 21.697368 3.26295109 5.33968050 May 17 -71.570551 3.70784344 -24.63729245 Jun 17 23.909090 3.71321954 50.17769058 Jul 17 32.266105 3.71859563 -23.58470060 Aug 17 18.176210 3.52381982 7.19997032 Sep 17 16.460484 3.32904400 -13.38952756 Oct 17 -21.035664 3.01056425 6.02510000 Nov 17 -1.415686 2.69208450 -10.37639852 Dec 17 -73.308116 2.69679034 17.41132588 Jan 18 -8.707364 2.70149619 -17.09413249 Feb 18 23.443477 3.12752571 20.72899698 Mar 18 40.084647 3.55355523 -22.93820221 Apr 18 21.697368 4.10694765 1.99568393 May 18 -71.570551 4.66034007 -17.38978908 Jun 18 23.909090 5.52306684 33.36784327 Jul 18 32.266105 6.38579361 -12.25189859 Aug 18 18.176210 6.55778715 7.56600298 Sep 18 16.460484 6.72978069 -9.89026425 Oct 18 -21.035664 5.82393854 -2.68827428 Nov 18 -1.415686 4.91809638 6.49758960 Dec 18 -73.308116 3.98960115 23.71851507 Jan 19 -8.707364 3.06110591 19.14625778 Feb 19 23.443477 2.51525598 -14.05873330 Mar 19 40.084647 1.96940605 -16.05405304 Apr 19 21.697368 1.32945357 -29.32682199 May 19 -71.570551 0.68950109 -9.01895010 Jun 19 23.909090 0.46531441 29.82559570 Jul 19 32.266105 0.24112773 -9.60723270 Aug 19 18.176210 0.78511846 12.83867168 Sep 19 16.460484 1.32910918 -13.98959274 Oct 19 -21.035664 1.22159499 8.41406926 Nov 19 -1.415686 1.11408080 -8.29839482 Dec 19 -73.308116 0.02990139 23.87821484 Jan 20 -8.707364 -1.05427803 7.26164173 Feb 20 23.443477 -2.04119246 1.59771515 Mar 20 40.084647 -3.02810690 -8.05654009 Apr 20 21.697368 -2.96675002 1.86938160 May 20 -71.570551 -2.90539314 -42.52405587 Jun 20 23.909090 -2.09295517 16.08386529 Jul 20 32.266105 -1.28051721 -0.28558776 Aug 20 18.176210 -0.06293418 -13.41327569 Sep 20 16.460484 1.15464886 -23.31513241 Oct 20 -21.035664 1.64363718 24.29202708 Nov 20 -1.415686 2.13262550 17.58306048 Dec 20 -73.308116 2.22573284 35.68238338 Jan 21 -8.707364 2.31884019 -14.91147649 Feb 21 23.443477 2.11139024 10.24513245 Mar 21 40.084647 1.90394028 1.81141273 Apr 21 21.697368 1.60946428 -4.60683270 May 21 -71.570551 1.31498828 -60.84443729 Jun 21 23.909090 1.27334164 14.61756848 Jul 21 32.266105 1.23169499 11.00220004 Aug 21 18.176210 1.64259740 -3.31880727 Sep 21 16.460484 2.05349981 -8.81398337 Oct 21 -21.035664 1.98064386 12.45502039 Nov 21 -1.415686 1.90778791 15.30789807 Dec 21 -73.308116 1.08370451 26.52441172 Jan 22 -8.707364 0.25962110 3.64774259 Feb 22 23.443477 -1.16339058 -4.68008674 Mar 22 40.084647 -2.58640225 -16.99824473 Apr 22 21.697368 -3.35541858 5.85805016 May 22 -71.570551 -4.12443490 -33.30501411 Jun 22 23.909090 -4.95585803 1.84676814 Jul 22 32.266105 -5.78728116 4.72117618 Aug 22 18.176210 -6.41325817 -20.56295170 Sep 22 16.460484 -7.03923518 2.37875162 Oct 22 -21.035664 -7.86491733 41.90058158 Nov 22 -1.415686 -8.69059947 18.40628545 Dec 22 -73.308116 -9.69873474 5.10685096 Jan 23 -8.707364 -10.70687000 -19.38576630 Feb 23 23.443477 -12.17444325 -5.16903406 Mar 23 40.084647 -13.64201650 -8.34263049 Apr 23 21.697368 -14.90292784 10.00555943 May 23 -71.570551 -16.16383919 -40.76560982 Jun 23 23.909090 -15.73342310 7.72433322 Jul 23 32.266105 -15.30300702 12.03690205 Aug 23 18.176210 -13.19975602 -12.17645384 Sep 23 16.460484 -11.09650503 -2.06397853 Oct 23 -21.035664 -9.31094236 -4.45339339 Nov 23 -1.415686 -7.52537969 6.04106567 Dec 23 -73.308116 -6.47554512 1.98366134 Jan 24 -8.707364 -5.42571054 11.33307424 Feb 24 23.443477 -4.55381251 7.81033520 Mar 24 40.084647 -3.68191447 11.69726749 Apr 24 21.697368 -2.74808823 11.05071981 May 24 -71.570551 -1.81426198 -36.21518703 Jun 24 23.909090 -1.34908877 -6.56000112 Jul 24 32.266105 -0.88391556 -4.48218942 Aug 24 18.176210 -0.36547710 4.28926723 Sep 24 16.460484 0.15296137 10.38655508 Oct 24 -21.035664 0.74488751 -4.20922326 Nov 24 -1.415686 1.33681366 12.07887232 Dec 24 -73.308116 1.59103346 -3.48291724 Jan 25 -8.707364 1.84525326 10.36211044 Feb 25 23.443477 1.77049090 -5.51396821 Mar 25 40.084647 1.69572854 10.01962448 Apr 25 21.697368 2.44395990 11.15867168 May 25 -71.570551 3.19219126 -39.82164027 Jun 25 23.909090 4.00943495 -2.61852483 Jul 25 32.266105 4.82667864 -5.49278361 Aug 25 18.176210 5.28025046 -3.55646033 Sep 25 16.460484 5.73382229 -3.39430584 Oct 25 -21.035664 5.89129915 35.54436511 Nov 25 -1.415686 6.04877601 10.36690997 Dec 25 -73.308116 5.84954534 11.55857088 Jan 26 -8.707364 5.65031468 -13.94295099 Feb 26 23.443477 4.62784713 5.22867556 Mar 26 40.084647 3.60537958 -9.89002656 Apr 26 21.697368 2.11095222 13.69167937 May 26 -71.570551 0.61652485 -33.84597386 Jun 26 23.909090 -0.56595883 6.35686895 Jul 26 32.266105 -1.74844252 3.68233754 Aug 26 18.176210 -1.92561031 -11.95059956 Sep 26 16.460484 -2.10277810 25.84229454 Oct 26 -21.035664 -2.62214129 -5.64219446 Nov 26 -1.415686 -3.14150447 4.35719045 Dec 26 -73.308116 -4.38393582 -17.30794795 Jan 27 -8.707364 -5.62636717 1.13373087 Feb 27 23.443477 -7.61178495 22.66830763 Mar 27 40.084647 -9.59720272 14.91255573 Apr 27 21.697368 -12.76139549 6.76402707 May 27 -71.570551 -15.92558826 -36.10386075 Jun 27 23.909090 -20.23877396 8.32968407 Jul 27 32.266105 -24.55195966 29.78585468 Aug 27 18.176210 -27.26774385 -22.60846601 Sep 27 16.460484 -29.98352805 29.32304449 Oct 27 -21.035664 -29.86491279 -13.19942296 Nov 27 -1.415686 -29.74629752 -10.93801650 Dec 27 -73.308116 -27.65612694 -106.43575684 Jan 28 -8.707364 -25.56595635 21.37332004 Feb 28 23.443477 -22.06027944 -6.38319787 Mar 28 40.084647 -18.55460253 32.36995554 Apr 28 21.697368 -13.46920877 11.47184035 May 28 -71.570551 -8.38381501 -14.64563400 Jun 28 23.909090 -3.64124243 15.73215255 Jul 28 32.266105 1.10133014 17.93256489 Aug 28 18.176210 3.98866072 -4.76487059 Sep 28 16.460484 6.87599130 4.46352514 Oct 28 -21.035664 7.61285269 14.72281157 Nov 28 -1.415686 8.34971407 -3.33402809 Dec 28 -73.308116 7.24628053 -31.83816431 Jan 29 -8.707364 6.14284699 16.66451670 Feb 29 23.443477 4.71972892 22.63679376 Mar 29 40.084647 3.29661085 20.11874216 Apr 29 21.697368 2.46541823 34.43721336 May 29 -71.570551 1.63422560 -65.16367461 Jun 29 23.909090 0.69734715 -16.80643703 Jul 29 32.266105 -0.23953130 -6.52657367 Aug 29 18.176210 -0.08782860 11.51161873 Sep 29 16.460484 0.06387411 2.77564233 Oct 29 -21.035664 1.36402116 -6.52835690 Nov 29 -1.415686 2.66416820 6.05151777 Dec 29 -73.308116 3.93252602 -13.22440979 Jan 30 -8.707364 5.20088383 -22.59352014 Feb 30 23.443477 5.51619317 26.34032952 Mar 30 40.084647 5.83150250 52.88385052 Apr 30 21.697368 6.68092177 13.32170981 May 30 -71.570551 7.53034104 -66.15979004 Jun 30 23.909090 7.91983308 19.37107704 Jul 30 32.266105 8.30932512 -22.17543009 Aug 30 18.176210 8.21243837 5.61135176 Sep 30 16.460484 8.11555162 -2.97603518 Oct 30 -21.035664 7.94544673 0.59021752 Nov 30 -1.415686 7.77534184 40.24034414 Dec 30 -73.308116 7.52916667 -35.92105045 Jan 31 -8.707364 7.28299151 17.22437219 Feb 31 23.443477 6.41389760 -3.85737491 Mar 31 40.084647 5.54480369 33.47054933 Apr 31 21.697368 4.65331174 -3.25068016 May 31 -71.570551 3.76181980 -19.09126881 Jun 31 23.909090 2.64232036 -37.75141025 Jul 31 32.266105 1.52282093 16.91107410 Aug 31 18.176210 0.38625511 -5.16246497 Sep 31 16.460484 -0.75031072 17.98982716 Oct 31 -21.035664 -1.77997567 5.91563992 Nov 31 -1.415686 -2.80964062 -5.37467340 > m$win s t l 3711 19 13 > m$deg s t l 0 1 1 > m$jump s t l 372 2 2 > m$inner [1] 2 > m$outer [1] 0 > postscript(file="/var/www/rcomp/tmp/11pk71322149571.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m,main=main) > dev.off() null device 1 > mylagmax <- nx/2 > postscript(file="/var/www/rcomp/tmp/22asl1322149571.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > acf(as.numeric(x),lag.max = mylagmax,main='Observed') > acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend') > acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal') > acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder') > par(op) > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/30n5k1322149571.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(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') > spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') > spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') > par(op) > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4kzb61322149571.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(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend') > cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal') > cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder') > par(op) > dev.off() null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Component',header=TRUE) > a<-table.element(a,'Window',header=TRUE) > a<-table.element(a,'Degree',header=TRUE) > a<-table.element(a,'Jump',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Seasonal',header=TRUE) > a<-table.element(a,m$win['s']) > a<-table.element(a,m$deg['s']) > a<-table.element(a,m$jump['s']) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Trend',header=TRUE) > a<-table.element(a,m$win['t']) > a<-table.element(a,m$deg['t']) > a<-table.element(a,m$jump['t']) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Low-pass',header=TRUE) > a<-table.element(a,m$win['l']) > a<-table.element(a,m$deg['l']) > a<-table.element(a,m$jump['l']) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/51gnw1322149571.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Seasonal',header=TRUE) > a<-table.element(a,'Trend',header=TRUE) > a<-table.element(a,'Remainder',header=TRUE) > a<-table.row.end(a) > for (i in 1:nx) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]+m$time.series[i,'remainder']) + a<-table.element(a,m$time.series[i,'seasonal']) + a<-table.element(a,m$time.series[i,'trend']) + a<-table.element(a,m$time.series[i,'remainder']) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/6oq9z1322149571.tab") > > try(system("convert tmp/11pk71322149571.ps tmp/11pk71322149571.png",intern=TRUE)) character(0) > try(system("convert tmp/22asl1322149571.ps tmp/22asl1322149571.png",intern=TRUE)) character(0) > try(system("convert tmp/30n5k1322149571.ps tmp/30n5k1322149571.png",intern=TRUE)) character(0) > try(system("convert tmp/4kzb61322149571.ps tmp/4kzb61322149571.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.90 0.17 5.08