R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(235.1 + ,280.7 + ,264.6 + ,240.7 + ,201.4 + ,240.8 + ,241.1 + ,223.8 + ,206.1 + ,174.7 + ,203.3 + ,220.5 + ,299.5 + ,347.4 + ,338.3 + ,327.7 + ,351.6 + ,396.6 + ,438.8 + ,395.6 + ,363.5 + ,378.8 + ,357 + ,369 + ,464.8 + ,479.1 + ,431.3 + ,366.5 + ,326.3 + ,355.1 + ,331.6 + ,261.3 + ,249 + ,205.5 + ,235.6 + ,240.9 + ,264.9 + ,253.8 + ,232.3 + ,193.8 + ,177 + ,213.2 + ,207.2 + ,180.6 + ,188.6 + ,175.4 + ,199 + ,179.6 + ,225.8 + ,234 + ,200.2 + ,183.6 + ,178.2 + ,203.2 + ,208.5 + ,191.8 + ,172.8 + ,148 + ,159.4 + ,154.5 + ,213.2 + ,196.4 + ,182.8 + ,176.4 + ,153.6 + ,173.2 + ,171 + ,151.2 + ,161.9 + ,157.2 + ,201.7 + ,236.4 + ,356.1 + ,398.3 + ,403.7 + ,384.6 + ,365.8 + ,368.1 + ,367.9 + ,347 + ,343.3 + ,292.9 + ,311.5 + ,300.9 + ,366.9 + ,356.9 + ,329.7 + ,316.2 + ,269 + ,289.3 + ,266.2 + ,253.6 + ,233.8 + ,228.4 + ,253.6 + ,260.1 + ,306.6 + ,309.2 + ,309.5 + ,271 + ,279.9 + ,317.9 + ,298.4 + ,246.7 + ,227.3 + ,209.1 + ,259.9 + ,266 + ,320.6 + ,308.5 + ,282.2 + ,262.7 + ,263.5 + ,313.1 + ,284.3 + ,252.6 + ,250.3 + ,246.5 + ,312.7 + ,333.2 + ,446.4 + ,511.6 + ,515.5 + ,506.4 + ,483.2 + ,522.3 + ,509.8 + ,460.7 + ,405.8 + ,375 + ,378.5 + ,406.8 + ,467.8 + ,469.8 + ,429.8 + ,355.8 + ,332.7 + ,378 + ,360.5 + ,334.7 + ,319.5 + ,323.1 + ,363.6 + ,352.1 + ,411.9 + ,388.6 + ,416.4 + ,360.7 + ,338 + ,417.2 + ,388.4 + ,371.1 + ,331.5 + ,353.7 + ,396.7 + ,447 + ,533.5 + ,565.4 + ,542.3 + ,488.7 + ,467.1 + ,531.3 + ,496.1 + ,444 + ,403.4 + ,386.3 + ,394.1 + ,404.1 + ,462.1 + ,448.1 + ,432.3 + ,386.3 + ,395.2 + ,421.9 + ,382.9 + ,384.2 + ,345.5 + ,323.4 + ,372.6 + ,376 + ,462.7 + ,487 + ,444.2 + ,399.3 + ,394.9 + ,455.4 + ,414 + ,375.5 + ,347 + ,339.4 + ,385.8 + ,378.8 + ,451.8 + ,446.1 + ,422.5 + ,383.1 + ,352.8 + ,445.3 + ,367.5 + ,355.1 + ,326.2 + ,319.8 + ,331.8 + ,340.9 + ,394.1 + ,417.2 + ,369.9 + ,349.2 + ,321.4 + ,405.7 + ,342.9 + ,316.5 + ,284.2 + ,270.9 + ,288.8 + ,278.8 + ,324.4 + ,310.9 + ,299 + ,273 + ,279.3 + ,359.2 + ,305 + ,282.1 + ,250.3 + ,246.5 + ,257.9 + ,266.5 + ,315.9 + ,318.4 + ,295.4 + ,266.4 + ,245.8 + ,362.8 + ,324.9 + ,294.2 + ,289.5 + ,295.2 + ,290.3 + ,272 + ,307.4 + ,328.7 + ,292.9 + ,249.1 + ,230.4 + ,361.5 + ,321.7 + ,277.2 + ,260.7 + ,251 + ,257.6 + ,241.8 + ,287.5 + ,292.3 + ,274.7 + ,254.2 + ,230 + ,339 + ,318.2 + ,287 + ,295.8 + ,284 + ,271 + ,262.7 + ,340.6 + ,379.4 + ,373.3 + ,355.2 + ,338.4 + ,466.9 + ,451 + ,422 + ,429.2 + ,425.9 + ,460.7 + ,463.6 + ,541.4 + ,544.2 + ,517.5 + ,469.4 + ,439.4 + ,549 + ,533 + ,506.1 + ,484 + ,457 + ,481.5 + ,469.5 + ,544.7 + ,541.2 + ,521.5 + ,469.7 + ,434.4 + ,542.6 + ,517.3 + ,485.7 + ,465.8 + ,447 + ,426.6 + ,411.6 + ,467.5 + ,484.5 + ,451.2 + ,417.4 + ,379.9 + ,484.7 + ,455 + ,420.8 + ,416.5 + ,376.3 + ,405.6 + ,405.8 + ,500.8 + ,514 + ,475.5 + ,430.1 + ,414.4 + ,538 + ,526 + ,488.5 + ,520.2 + ,504.4 + ,568.5 + ,610.6 + ,818 + ,830.9 + ,835.9 + ,782 + ,762.3 + ,856.9 + ,820.9 + ,769.6 + ,752.2 + ,724.4 + ,723.1 + ,719.5 + ,817.4 + ,803.3 + ,752.5 + ,689 + ,630.4 + ,765.5 + ,757.7 + ,732.2 + ,702.6 + ,683.3 + ,709.5 + ,702.2 + ,784.8 + ,810.9 + ,755.6 + ,656.8 + ,615.1 + ,745.3 + ,694.1 + ,675.7 + ,643.7 + ,622.1 + ,634.6 + ,588 + ,689.7 + ,673.9 + ,647.9 + ,568.8 + ,545.7 + ,632.6 + ,643.8 + ,593.1 + ,579.7 + ,546 + ,562.9 + ,572.5) > par8 = 'FALSE' > par7 = '1' > par6 = '' > par5 = '1' > par4 = '' > par3 = '0' > par2 = 'periodic' > par1 = '12' > main = 'Seasonal Decomposition by Loess' > par8 <- 'FALSE' > par7 <- '1' > par6 <- '' > par5 <- '1' > par4 <- '' > par3 <- '0' > par2 <- 'periodic' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > par1 <- as.numeric(par1) #seasonal period > if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window > par3 <- as.numeric(par3) #s.degree > if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window > par5 <- as.numeric(par5)#t.degree > if (par6 != '') par6 <- as.numeric(par6)#l.window > par7 <- as.numeric(par7)#l.degree > if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust > nx <- length(x) > x <- ts(x,frequency=par1) > if (par6 != '') { + m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8) + } else { + m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8) + } > m$time.series seasonal trend remainder Jan 1 45.72725 209.6437 -20.27090547 Feb 1 54.38367 213.2173 13.09906119 Mar 1 30.87559 216.7909 16.93353478 Apr 1 -9.14412 220.7913 29.05280230 May 1 -30.77997 224.7918 7.38820069 Jun 1 41.06930 229.2886 -29.55792205 Jul 1 17.42177 233.7855 -10.10725016 Aug 1 -14.52484 238.4775 -0.15268528 Sep 1 -32.43275 243.1696 -4.63682018 Oct 1 -48.77996 250.2251 -26.74516269 Nov 1 -27.61427 257.2807 -26.36640366 Dec 1 -26.20169 270.4281 -23.72636888 Jan 2 45.72725 283.5754 -29.80269557 Feb 2 54.38367 299.2267 -6.21033519 Mar 2 30.87559 314.8779 -7.45346787 Apr 2 -9.14412 330.5198 6.32431133 May 2 -30.77997 346.1617 36.21822142 Jun 2 41.06930 359.6890 -4.15831558 Jul 2 17.42177 373.2163 48.16194206 Aug 2 -14.52484 382.6680 27.45685656 Sep 2 -32.43275 392.1197 3.81307127 Oct 2 -48.77996 395.2147 32.36525685 Nov 2 -27.61427 398.3097 -13.69545605 Dec 2 -26.20169 394.2304 0.97126578 Jan 3 45.72725 390.1511 28.92162614 Feb 3 54.38367 380.6245 44.09178164 Mar 3 30.87559 371.0980 29.32644407 Apr 3 -9.14412 358.7174 16.92668567 May 3 -30.77997 346.3369 10.74305815 Jun 3 41.06930 331.8457 -17.81499658 Jul 3 17.42177 317.3545 -3.17625667 Aug 3 -14.52484 301.3009 -25.47607901 Sep 3 -32.43275 285.2473 -3.81460113 Oct 3 -48.77996 270.8190 -16.53900414 Nov 3 -27.61427 256.3906 6.82369437 Dec 3 -26.20169 245.0545 22.04717893 Jan 4 45.72725 233.7185 -14.54569797 Feb 4 54.38367 225.8595 -26.44319984 Mar 4 30.87559 218.0006 -16.57619477 Apr 4 -9.14412 213.5060 -10.56187803 May 4 -30.77997 209.0114 -1.23143041 Jun 4 41.06930 206.4762 -34.34551084 Jul 4 17.42177 203.9410 -14.16279665 Aug 4 -14.52484 202.2901 -7.16529478 Sep 4 -32.43275 200.6392 20.39350731 Oct 4 -48.77996 199.5718 24.60814111 Nov 4 -27.61427 198.5044 28.10987643 Dec 4 -26.20169 197.6045 8.19722256 Jan 5 45.72725 196.7045 -16.63179278 Feb 5 54.38367 195.5050 -15.88863222 Mar 5 30.87559 194.3054 -24.98096471 Apr 5 -9.14412 192.7677 -0.02362096 May 5 -30.77997 191.2301 17.74985367 Jun 5 41.06930 189.9383 -27.80762943 Jul 5 17.42177 188.6465 2.43168210 Aug 5 -14.52484 187.0044 19.32042171 Sep 5 -32.43275 185.3623 19.87046153 Oct 5 -48.77996 183.2488 13.53110943 Nov 5 -27.61427 181.1354 5.87885886 Dec 5 -26.20169 178.2225 2.47915021 Jan 6 45.72725 175.3097 -7.83691992 Feb 6 54.38367 172.8279 -30.81152670 Mar 6 30.87559 170.3460 -18.42162656 Apr 6 -9.14412 171.2302 14.31387913 May 6 -30.77997 172.1144 12.26551570 Jun 6 41.06930 179.4281 -47.29743855 Jul 6 17.42177 186.7418 -33.16359817 Aug 6 -14.52484 200.9758 -35.25099103 Sep 6 -32.43275 215.2098 -20.87708367 Oct 6 -48.77996 233.8573 -27.87735236 Nov 6 -27.61427 252.5048 -23.19051952 Dec 6 -26.20169 271.4765 -8.87481041 Jan 7 45.72725 290.4482 19.92453723 Feb 7 54.38367 306.9047 37.01159205 Mar 7 30.87559 323.3613 49.46315381 Apr 7 -9.14412 334.4814 59.26275569 May 7 -30.77997 345.6015 50.97848844 Jun 7 41.06930 349.4733 -22.44259766 Jul 7 17.42177 353.3451 -2.86688912 Aug 7 -14.52484 350.3492 11.17567370 Sep 7 -32.43275 347.3532 28.37953674 Oct 7 -48.77996 341.2545 0.42543191 Nov 7 -27.61427 335.1558 3.95842860 Dec 7 -26.20169 327.6966 -0.59489765 Jan 8 45.72725 320.2373 0.93541463 Feb 8 54.38367 312.1545 -9.63816180 Mar 8 30.87559 304.0716 -5.24723130 Apr 8 -9.14412 297.3134 28.03068284 May 8 -30.77997 290.5552 9.22472785 Jun 8 41.06930 285.9095 -37.67881633 Jul 8 17.42177 281.2638 -32.48556589 Aug 8 -14.52484 277.9015 -9.77669919 Sep 8 -32.43275 274.5393 -8.30653228 Oct 8 -48.77996 273.4963 3.68365776 Nov 8 -27.61427 272.4533 8.76094932 Dec 8 -26.20169 273.6221 12.67954801 Jan 9 45.72725 274.7910 -13.91821478 Feb 9 54.38367 275.4517 -20.63534996 Mar 9 30.87559 276.1124 2.51202180 Apr 9 -9.14412 275.8029 4.34118050 May 9 -30.77997 275.4935 35.18647008 Jun 9 41.06930 275.5752 1.25552599 Jul 9 17.42177 275.6569 5.32137653 Aug 9 -14.52484 275.1637 -13.93886097 Sep 9 -32.43275 274.6705 -14.93779826 Oct 9 -48.77996 273.4873 -15.60736534 Nov 9 -27.61427 272.3041 15.21016910 Dec 9 -26.20169 271.7473 20.45434662 Jan 10 45.72725 271.1906 3.68216266 Feb 10 54.38367 271.7971 -17.68081730 Mar 10 30.87559 272.4037 -21.07929033 Apr 10 -9.14412 274.8468 -3.00272537 May 10 -30.77997 277.2900 16.98997046 Jun 10 41.06930 284.2799 -12.24921285 Jul 10 17.42177 291.2698 -24.39160153 Aug 10 -14.52484 305.3970 -38.27211642 Sep 10 -32.43275 319.5241 -36.79133110 Oct 10 -48.77996 338.9159 -43.63596830 Nov 10 -27.61427 358.3078 -17.99350398 Dec 10 -26.20169 378.9301 -19.52838075 Jan 11 45.72725 399.5524 1.12038101 Feb 11 54.38367 417.2912 39.92514868 Mar 11 30.87559 435.0300 49.59442329 Apr 11 -9.14412 445.7243 69.81981419 May 11 -30.77997 456.4186 57.56133598 Jun 11 41.06930 459.0611 22.16958918 Jul 11 17.42177 461.7036 30.67463702 Aug 11 -14.52484 456.9366 18.28821122 Sep 11 -32.43275 452.1697 -13.93691437 Oct 11 -48.77996 442.0728 -18.29283679 Nov 11 -27.61427 431.9759 -25.86165770 Dec 11 -26.20169 420.4012 12.60047989 Jan 12 45.72725 408.8265 13.24625600 Feb 12 54.38367 399.1510 16.26529601 Mar 12 30.87559 389.4756 9.44884295 Apr 12 -9.14412 383.2452 -18.30111861 May 12 -30.77997 377.0149 -13.53494929 Jun 12 41.06930 372.7229 -35.79222958 Jul 12 17.42177 368.4309 -25.35271524 Aug 12 -14.52484 365.7562 -16.53135376 Sep 12 -32.43275 363.0814 -11.14869207 Oct 12 -48.77996 363.1979 8.68204031 Nov 12 -27.61427 363.3144 27.89987422 Dec 12 -26.20169 365.2627 13.03895964 Jan 13 45.72725 367.2111 -1.03831642 Feb 13 54.38367 369.0179 -34.80153384 Mar 13 30.87559 370.8246 14.69975566 Apr 13 -9.14412 373.4334 -3.58926916 May 13 -30.77997 376.0421 -7.26216312 Jun 13 41.06930 382.7177 -6.58703495 Jul 13 17.42177 389.3933 -18.41511215 Aug 13 -14.52484 400.4929 -14.86810261 Sep 13 -32.43275 411.5925 -47.65979286 Oct 13 -48.77996 423.7739 -21.29390470 Nov 13 -27.61427 435.9552 -11.64091502 Dec 13 -26.20169 447.0118 26.18993652 Jan 14 45.72725 458.0683 29.70442658 Feb 14 54.38367 465.5517 45.46466455 Mar 14 30.87559 473.0350 38.38940946 Apr 14 -9.14412 474.7460 23.09816729 May 14 -30.77997 476.4569 21.42305599 Jun 14 41.06930 471.9889 18.24177057 Jul 14 17.42177 467.5210 11.15727978 Aug 14 -14.52484 459.2404 -0.71553105 Sep 14 -32.43275 450.9598 -15.12704166 Oct 14 -48.77996 442.3013 -7.22130841 Nov 14 -27.61427 433.6427 -11.92847363 Dec 14 -26.20169 425.9348 4.36685148 Jan 15 45.72725 418.2269 -1.85418489 Feb 15 54.38367 412.1133 -18.39693339 Mar 15 30.87559 405.9996 -4.57517496 Apr 15 -9.14412 401.8111 -6.36700775 May 15 -30.77997 397.6227 28.35729033 Jun 15 41.06930 395.9692 -15.13850615 Jul 15 17.42177 394.3157 -28.83750799 Aug 15 -14.52484 395.0334 3.69140934 Sep 15 -32.43275 395.7511 -17.81837312 Oct 15 -48.77996 397.6340 -25.45406909 Nov 15 -27.61427 399.5169 0.69733646 Dec 15 -26.20169 401.6887 0.51302195 Jan 16 45.72725 403.8604 13.11234595 Feb 16 54.38367 405.2406 27.37574971 Mar 16 30.87559 406.6207 6.70366040 Apr 16 -9.14412 406.7142 1.72995279 May 16 -30.77997 406.8076 18.87237606 Jun 16 41.06930 405.8739 8.45675736 Jul 16 17.42177 404.9403 -8.36206671 Aug 16 -14.52484 403.1557 -13.13090143 Sep 16 -32.43275 401.3712 -21.93843593 Oct 16 -48.77996 399.4962 -11.31621011 Nov 16 -27.61427 397.6212 15.79311723 Dec 16 -26.20169 395.8086 9.19304281 Jan 17 45.72725 393.9961 12.07660692 Feb 17 54.38367 391.8749 -0.15854253 Mar 17 30.87559 389.7536 1.87081496 Apr 17 -9.14412 386.6828 5.56132938 May 17 -30.77997 383.6120 -0.03202533 Jun 17 41.06930 379.8355 24.39518598 Jul 17 17.42177 376.0590 -25.98080808 Aug 17 -14.52484 372.3806 -2.75573659 Sep 17 -32.43275 368.7021 -10.06936488 Oct 17 -48.77996 365.5619 3.01810007 Nov 17 -27.61427 362.4216 -3.00733345 Dec 17 -26.20169 359.8168 7.28490386 Jan 18 45.72725 357.2120 -8.83922030 Feb 18 54.38367 354.3830 8.43332454 Mar 18 30.87559 351.5540 -12.52962367 Apr 18 -9.14412 347.7592 10.58494652 May 18 -30.77997 343.9643 8.21564759 Jun 18 41.06930 338.8473 25.78336247 Jul 18 17.42177 333.7304 -8.25212802 Aug 18 -14.52484 327.0629 3.96194568 Sep 18 -32.43275 320.3954 -3.76268040 Oct 18 -48.77996 314.0780 5.60193272 Nov 18 -27.61427 307.7606 8.65364737 Dec 18 -26.20169 303.3915 1.61018538 Jan 19 45.72725 299.0224 -20.34963808 Feb 19 54.38367 296.2989 -39.78261452 Mar 19 30.87559 293.5755 -25.45108403 Apr 19 -9.14412 291.9236 -9.77951073 May 19 -30.77997 290.2718 19.80819345 Jun 19 41.06930 289.7665 28.36416371 Jul 19 17.42177 289.2613 -1.68307140 Aug 19 -14.52484 288.7719 7.85290337 Sep 19 -32.43275 288.2826 -5.54982163 Oct 19 -48.77996 286.8520 8.42796042 Nov 19 -27.61427 285.4214 0.09284401 Dec 19 -26.20169 284.8059 7.89581562 Jan 20 45.72725 284.1903 -14.01757424 Feb 20 54.38367 285.8763 -21.86001920 Mar 20 30.87559 287.5624 -23.03795723 Apr 20 -9.14412 290.7120 -15.16791154 May 20 -30.77997 293.8617 -17.28173498 Jun 20 41.06930 296.4006 25.33011244 Jul 20 17.42177 298.9395 8.53875450 Aug 20 -14.52484 299.5874 9.13744833 Sep 20 -32.43275 300.2353 21.69744238 Oct 20 -48.77996 298.7384 45.24159336 Nov 20 -27.61427 297.2414 20.67284586 Dec 20 -26.20169 295.0652 3.13644766 Jan 21 45.72725 292.8891 -31.21631202 Feb 21 54.38367 290.6997 -16.38338635 Mar 21 30.87559 288.5104 -26.48595374 Apr 21 -9.14412 286.7407 -28.49659812 May 21 -30.77997 284.9711 -23.79111162 Jun 21 41.06930 283.7339 36.69683353 Jul 21 17.42177 282.4967 21.78157330 Aug 21 -14.52484 281.0390 10.68583046 Sep 21 -32.43275 279.5814 13.55138783 Oct 21 -48.77996 277.5016 22.27837801 Nov 21 -27.61427 275.4218 9.79246972 Dec 21 -26.20169 273.8064 -5.80466174 Jan 22 45.72725 272.1909 -30.41815467 Feb 22 54.38367 272.7522 -34.83585311 Mar 22 30.87559 273.3134 -29.48904461 Apr 22 -9.14412 276.3152 -12.97103997 May 22 -30.77997 279.3169 -18.53690445 Jun 22 41.06930 283.8227 14.10796047 Jul 22 17.42177 288.3286 12.44962003 Aug 22 -14.52484 294.4332 7.09166281 Sep 22 -32.43275 300.5377 27.69500581 Oct 22 -48.77996 307.9595 24.82046264 Nov 22 -27.61427 315.3812 -16.76697900 Dec 22 -26.20169 324.5680 -35.66628456 Jan 23 45.72725 333.7547 -38.88195160 Feb 23 54.38367 345.1918 -20.17550548 Mar 23 30.87559 356.6290 -14.20455243 Apr 23 -9.14412 370.9949 -6.65080261 May 23 -30.77997 385.3609 -16.18092192 Jun 23 41.06930 401.5741 24.25663153 Jul 23 17.42177 417.7873 15.79097961 Aug 23 -14.52484 432.0971 4.42774398 Sep 23 -32.43275 446.4069 15.22580856 Oct 23 -48.77996 456.5070 18.17291664 Nov 23 -27.61427 466.6071 21.70712624 Dec 23 -26.20169 473.5735 16.22815529 Jan 24 45.72725 480.5399 15.13282287 Feb 24 54.38367 485.5948 4.22147979 Mar 24 30.87559 490.6498 -4.02535636 Apr 24 -9.14412 493.8130 -15.26891290 May 24 -30.77997 496.9763 -26.79633857 Jun 24 41.06930 498.4739 9.45679179 Jul 24 17.42177 499.9715 15.60671679 Aug 24 -14.52484 500.6162 20.00867369 Sep 24 -32.43275 501.2608 15.17193080 Oct 24 -48.77996 500.7977 4.98222086 Nov 24 -27.61427 500.3347 8.77961245 Dec 24 -26.20169 498.8225 -3.12079604 Jan 25 45.72725 497.3103 1.66243399 Feb 25 54.38367 495.5953 -8.77900771 Mar 25 30.87559 493.8803 -3.25594248 Apr 25 -9.14412 491.9053 -13.06118154 May 25 -30.77997 489.9303 -24.75028972 Jun 25 41.06930 486.2436 15.28708152 Jul 25 17.42177 482.5570 17.32124739 Aug 25 -14.52484 477.4425 22.78235303 Sep 25 -32.43275 472.3280 25.90475889 Oct 25 -48.77996 466.4966 29.28335366 Nov 25 -27.61427 460.6652 -6.45095005 Dec 25 -26.20169 454.6475 -16.84580409 Jan 26 45.72725 448.6298 -26.85701961 Feb 26 54.38367 443.4464 -13.33006875 Mar 26 30.87559 438.2630 -17.93861095 Apr 26 -9.14412 435.3552 -8.81107911 May 26 -30.77997 432.4474 -21.76741639 Jun 26 41.06930 432.5368 11.09391952 Jul 26 17.42177 432.6262 4.95205007 Aug 26 -14.52484 434.4951 0.82978652 Sep 26 -32.43275 436.3639 12.56882318 Oct 26 -48.77996 438.6426 -13.56260833 Nov 26 -27.61427 440.9212 -7.70693830 Dec 26 -26.20169 444.5958 -12.59406354 Jan 27 45.72725 448.2703 6.80244975 Feb 27 54.38367 454.8643 4.75206970 Mar 27 30.87559 461.4582 -16.83380343 Apr 27 -9.14412 472.3586 -33.11449211 May 27 -30.77997 483.2590 -38.07904992 Jun 27 41.06930 501.3213 -4.39061960 Jul 27 17.42177 519.3836 -10.80539465 Aug 27 -14.52484 545.5950 -42.57018340 Sep 27 -32.43275 571.8064 -19.17367194 Oct 27 -48.77996 602.0871 -48.90715649 Nov 27 -27.61427 632.3678 -36.25353951 Dec 27 -26.20169 661.2280 -24.42630006 Jan 28 45.72725 690.0882 82.18457793 Feb 28 54.38367 714.2016 62.31468142 Mar 28 30.87559 738.3151 66.70929185 Apr 28 -9.14412 754.3769 36.76723424 May 28 -30.77997 770.4387 22.64130752 Jun 28 41.06930 776.2605 39.57021830 Jul 28 17.42177 782.0823 21.39592372 Aug 28 -14.52484 779.2330 4.89182621 Sep 28 -32.43275 776.3837 8.24902891 Oct 28 -48.77996 768.8600 4.31995604 Nov 28 -27.61427 761.3363 -10.62201530 Dec 28 -26.20169 753.4096 -7.70793076 Jan 29 45.72725 745.4830 26.18979231 Feb 29 54.38367 740.1602 8.75615569 Mar 29 30.87559 734.8374 -13.21297400 Apr 29 -9.14412 731.9718 -33.82770471 May 29 -30.77997 729.1063 -67.92630454 Jun 29 41.06930 727.9371 -3.50643897 Jul 29 17.42177 726.7680 13.51022124 Aug 29 -14.52484 727.0983 19.62654245 Sep 29 -32.43275 727.4286 7.60416388 Oct 29 -48.77996 726.8214 5.25851507 Nov 29 -27.61427 726.2143 10.89996777 Dec 29 -26.20169 722.8349 5.56674975 Jan 30 45.72725 719.4556 19.61717026 Feb 30 54.38367 714.1158 42.40055490 Mar 30 30.87559 708.7760 15.94844648 Apr 30 -9.14412 702.5465 -36.60241093 May 30 -30.77997 696.3171 -50.43713745 Jun 30 41.06930 688.4549 15.77575859 Jul 30 17.42177 680.5928 -3.91455073 Aug 30 -14.52484 672.2660 17.95886229 Sep 30 -32.43275 663.9392 12.19357552 Oct 30 -48.77996 655.9406 14.93931015 Nov 30 -27.61427 647.9421 14.27214631 Dec 30 -26.20169 640.2119 -26.01025379 Jan 31 45.72725 632.4818 11.49098464 Feb 31 54.38367 625.6721 -6.15575459 Mar 31 30.87559 618.8624 -1.83798689 Apr 31 -9.14412 615.2388 -37.29463141 May 31 -30.77997 611.6151 -35.13514505 Jun 31 41.06930 608.0351 -16.50443739 Jul 31 17.42177 604.4552 21.92306492 Aug 31 -14.52484 601.3190 6.30580716 Sep 31 -32.43275 598.1829 13.94984962 Oct 31 -48.77996 595.5043 -0.72438628 Nov 31 -27.61427 592.8258 -2.31152066 Dec 31 -26.20169 590.4126 8.28910924 > m$win s t l 3721 19 13 > m$deg s t l 0 1 1 > m$jump s t l 373 2 2 > m$inner [1] 2 > m$outer [1] 0 > postscript(file="/var/fisher/rcomp/tmp/1m0gw1352539660.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m,main=main) > dev.off() null device 1 > mylagmax <- nx/2 > postscript(file="/var/fisher/rcomp/tmp/2cni21352539660.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > acf(as.numeric(x),lag.max = mylagmax,main='Observed') > acf(as.numeric(m$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/fisher/rcomp/tmp/33t7k1352539660.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/fisher/rcomp/tmp/4mnqh1352539660.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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$jump['l']) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/5tdoz1352539660.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Seasonal',header=TRUE) > a<-table.element(a,'Trend',header=TRUE) > a<-table.element(a,'Remainder',header=TRUE) > a<-table.row.end(a) > for (i in 1:nx) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]+m$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/fisher/rcomp/tmp/6a4vg1352539660.tab") > > try(system("convert tmp/1m0gw1352539660.ps tmp/1m0gw1352539660.png",intern=TRUE)) character(0) > try(system("convert tmp/2cni21352539660.ps tmp/2cni21352539660.png",intern=TRUE)) character(0) > try(system("convert tmp/33t7k1352539660.ps tmp/33t7k1352539660.png",intern=TRUE)) character(0) > try(system("convert tmp/4mnqh1352539660.ps tmp/4mnqh1352539660.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.888 0.518 7.392