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(1021.3 + ,1039.79 + ,938.12 + ,947.36 + ,956.6 + ,956.6 + ,942.74 + ,951.98 + ,919.63 + ,901.15 + ,887.28 + ,836.45 + ,841.07 + ,836.45 + ,831.83 + ,817.97 + ,771.75 + ,707.05 + ,716.3 + ,725.54 + ,716.3 + ,707.05 + ,716.3 + ,780.99 + ,859.56 + ,961.22 + ,938.12 + ,988.95 + ,910.39 + ,901.15 + ,896.53 + ,910.39 + ,988.95 + ,988.95 + ,965.85 + ,975.09 + ,1002.82 + ,1025.92 + ,1081.38 + ,1164.56 + ,1201.53 + ,1229.26 + ,1275.47 + ,1275.47 + ,1307.82 + ,1252.36 + ,1261.61 + ,1340.17 + ,1414.11 + ,1409.49 + ,1432.59 + ,1520.4 + ,1529.64 + ,1455.7 + ,1427.97 + ,1538.88 + ,1612.82 + ,1635.93 + ,1603.58 + ,1589.72 + ,1557.37 + ,1589.72 + ,1668.28 + ,1635.93 + ,1615.68 + ,1644.69 + ,1622.71 + ,1626.11 + ,1705.55 + ,1841.35 + ,2029.03 + ,2024.21 + ,1952.87 + ,2153.06 + ,2339.29 + ,2502.89 + ,2515.37 + ,2445.68 + ,2491.11 + ,2691.32 + ,2651.8 + ,2593.49 + ,2697.23 + ,2751.63 + ,2713.9 + ,2747.21 + ,2982.32 + ,3063.39 + ,3058.7 + ,3074.38 + ,3341.06 + ,3500.03 + ,392.88 + ,3071.52 + ,2516.41 + ,2350.7 + ,2488.68 + ,2872.65 + ,3220.21 + ,3078.04 + ,3043.98 + ,3134.34 + ,3141.85 + ,3128.01 + ,3241.16 + ,3389.48 + ,3406.36 + ,3449.84 + ,3606.24 + ,3653.99 + ,3607.31 + ,3712.52 + ,3803.47 + ,3806.33 + ,3768.4 + ,3952.06 + ,4134.85 + ,4060.9 + ,3999.88 + ,4004.03 + ,3977.34 + ,3650.08 + ,3708.85 + ,3764.78 + ,3761.86 + ,3802.55 + ,3773.52 + ,3428.7 + ,3194.21 + ,3095.56 + ,3064.85 + ,3022.98 + ,2887.66 + ,3178.86 + ,3438.47 + ,3493.87 + ,3421.89 + ,3390.28 + ,3319.24 + ,3287.84 + ,3222.82 + ,3182.69 + ,3180.21 + ,3116.34 + ,3297.46 + ,3357.48 + ,3386.03 + ,3319.45 + ,3363.59 + ,3303.47 + ,3210.55 + ,3050.27 + ,3010.55 + ,3011.65 + ,3104.98 + ,3087.85 + ,3160.16 + ,3319.22 + ,3432.49 + ,3475.68 + ,3347.48 + ,3388.81 + ,3610.23 + ,3691.45 + ,3587.86 + ,3704.62 + ,3798.75 + ,3956.54 + ,4121.94 + ,4148.56 + ,4100.37 + ,4060.71 + ,4147.86 + ,3926.61 + ,3865.41 + ,3978.57 + ,3851.95 + ,3701.22 + ,3738.65 + ,3766.9 + ,3711.02 + ,3675.22 + ,3560.53 + ,3723.8 + ,3914.27 + ,3870.77 + ,3924.36 + ,3968.89 + ,3982.93 + ,3917.09 + ,3969.18 + ,4149.81 + ,4406.88 + ,423.82 + ,417.72 + ,4527.16 + ,4617.39 + ,4656.23 + ,4579.9 + ,4652.4 + ,4722.95 + ,4845.81 + ,4975.21 + ,5083.64 + ,5378.04 + ,5684.44 + ,5841.87 + ,5857.23 + ,6174.52 + ,6413.17 + ,6780.11 + ,6524.94 + ,6466.7 + ,6495.61 + ,6399.52 + ,6729.98 + ,7060.77 + ,7423.27 + ,8069.17 + ,8650.68 + ,8938.07 + ,9482.08 + ,10225.26 + ,9390.27 + ,8546.11 + ,8073.77 + ,8655.31 + ,9150.1 + ,9775.81 + ,9785.14 + ,9363.44 + ,9304.18 + ,9030.26 + ,8920.8 + ,8606.08 + ,8353.75 + ,8615.63 + ,8128.64 + ,8715.94 + ,8500.8 + ,8142.58 + ,7614.66 + ,7558.95 + ,7820.75 + ,7828.9 + ,7904.59 + ,8140.97 + ,8483.01 + ,8322.68 + ,8268.01 + ,8402.05 + ,8177.78 + ,7950.54 + ,8049.94 + ,7674.13 + ,7666.36 + ,7570.18 + ,7694.45 + ,7810.64 + ,7748.43 + ,7040.64 + ,7077.26 + ,7245.51 + ,7289.12 + ,7486.92 + ,7519.88 + ,7554.84 + ,7780.89 + ,7748.09 + ,7152.25 + ,6484.66 + ,6254.58 + ,5867.32 + ,5544.16 + ,5822.74 + ,5690.63 + ,5564.78 + ,5088.39 + ,4784.22 + ,5332.46 + ,5541.48 + ,5723.92 + ,5736.99 + ,5992.07 + ,6091.43 + ,6158.17 + ,6303.79 + ,6349.71 + ,6802.96 + ,7132.68 + ,7073.29 + ,7264.5 + ,7105.33 + ,7218.71 + ,7225.72 + ,7354.25 + ,7745.46 + ,8070.26 + ,8366.33 + ,8667.51 + ,8854.34 + ,9218.1 + ,9332.9 + ,9358.31 + ,9248.66 + ,9401.2 + ,9652.04 + ,9957.38 + ,10110.63 + ,10169.26 + ,10343.78 + ,10750.21 + ,11337.5 + ,11786.96 + ,12083.04 + ,12007.74 + ,11745.93 + ,11051.51 + ,11445.9 + ,11924.88 + ,12247.63 + ,12690.91 + ,12910.7 + ,13202.12 + ,13654.67 + ,13862.82 + ,13523.93 + ,14211.17 + ,14510.35 + ,14289.23 + ,14111.82 + ,13086.59 + ,13351.54 + ,13747.69 + ,12855.61 + ,12926.93 + ,12121.95 + ,11731.65 + ,11639.51 + ,12163.78 + ,12029.53 + ,11234.18 + ,9852.13 + ,9709.04 + ,9332.75 + ,7108.6 + ,6691.49 + ,6143.05 + ,6379.15 + ,5994.58 + ,5607.94 + ,6046.13 + ,6624.96 + ,6652.54 + ,6696 + ,7315.16 + ,7907.79 + ,8066.35 + ,7939.64 + ,8068.48 + ,8186.33 + ,7975.21 + ,8357.51 + ,8463.38 + ,7937.68 + ,8034.62 + ,8056.61 + ,8176.95 + ,8441.04 + ,8697.39 + ,8665.57 + ,8625.77 + ,8718.42 + ,8822.34 + ,8597.67 + ,8782.05 + ,8661.06 + ,8265.32 + ,8072.58 + ,721.85 + ,7138.6 + ,7351.11 + ,7077 + ,7272.37 + ,7577.84) > 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 59.68293 969.3686 -7.7515148 Feb 1 -74.44087 963.2670 150.9638836 Mar 1 -76.37045 957.1654 57.3250510 Apr 1 169.99975 950.6562 -173.2959154 May 1 160.38952 944.1469 -147.9364510 Jun 1 97.98395 935.8684 -77.2523492 Jul 1 73.58994 927.5899 -58.4398136 Aug 1 -172.21489 918.1460 206.0489313 Sep 1 -87.59234 908.7021 98.5202839 Oct 1 -68.20202 899.0076 70.3444046 Nov 1 -58.64592 889.3132 56.6127438 Dec 1 -24.17962 868.4651 -7.8354886 Jan 2 59.68293 847.6170 -66.2299715 Feb 2 -74.44087 824.4253 86.4655261 Mar 2 -76.37045 801.2337 106.9667927 Apr 2 169.99975 785.7990 -137.8287873 May 2 160.38952 770.3644 -159.0039366 Jun 2 97.98395 765.4706 -156.4045256 Jul 2 73.58994 760.5767 -117.8666809 Aug 2 -172.21489 769.1749 128.5800246 Sep 2 -87.59234 777.7730 26.1193377 Oct 2 -68.20202 793.7172 -18.4651960 Nov 2 -58.64592 809.6614 -34.7155112 Dec 2 -24.17962 824.4815 -19.3119176 Jan 3 59.68293 839.3016 -39.4245744 Feb 3 -74.44087 854.4207 181.2401482 Mar 3 -76.37045 869.5398 144.9506398 Apr 3 169.99975 888.6747 -69.7244690 May 3 160.38952 907.8096 -157.8091470 Jun 3 97.98395 923.8920 -120.7259969 Jul 3 73.58994 939.9745 -117.0344129 Aug 3 -172.21489 954.2983 128.3066329 Sep 3 -87.59234 968.6221 107.9202863 Oct 3 -68.20202 987.1405 70.0114676 Nov 3 -58.64592 1005.6590 18.8368674 Dec 3 -24.17962 1028.0602 -28.7906096 Jan 4 59.68293 1050.4614 -107.3243371 Feb 4 -74.44087 1075.1931 25.1677729 Mar 4 -76.37045 1099.9248 57.8256520 Apr 4 169.99975 1128.5391 -133.9788728 May 4 160.38952 1157.1534 -116.0129669 Jun 4 97.98395 1188.9402 -57.6641754 Jul 4 73.58994 1220.7270 -18.8469501 Aug 4 -172.21489 1253.8178 193.8670495 Sep 4 -87.59234 1286.9087 108.5036567 Oct 4 -68.20202 1315.4215 5.1404883 Nov 4 -58.64592 1343.9344 -23.6784616 Dec 4 -24.17962 1362.9228 1.4267732 Jan 5 59.68293 1381.9113 -27.4842426 Feb 5 -74.44087 1400.2368 83.6940495 Mar 5 -76.37045 1418.5623 90.3981106 Apr 5 169.99975 1444.0351 -93.6348027 May 5 160.38952 1469.5078 -100.2572852 Jun 5 97.98395 1493.3470 -135.6309657 Jul 5 73.58994 1517.1863 -162.8062123 Aug 5 -172.21489 1536.8147 174.2802076 Sep 5 -87.59234 1556.4431 143.9692351 Oct 5 -68.20202 1571.7013 132.4306803 Nov 5 -58.64592 1586.9596 75.2663440 Dec 5 -24.17962 1595.2678 18.6317958 Jan 6 59.68293 1603.5761 -105.8890028 Feb 6 -74.44087 1609.1158 55.0450374 Mar 6 -76.37045 1614.6556 129.9948468 Apr 6 169.99975 1632.8080 -166.8777101 May 6 160.38952 1650.9603 -195.6698362 Jun 6 97.98395 1685.6584 -138.9523451 Jul 6 73.58994 1720.3565 -171.2364203 Aug 6 -172.21489 1772.4142 25.9107091 Sep 6 -87.59234 1824.4719 -31.3295539 Oct 6 -68.20202 1892.1048 17.4472642 Nov 6 -58.64592 1959.7376 127.9383008 Dec 6 -24.17962 2033.6996 14.6899884 Jan 7 59.68293 2107.6616 -214.4745746 Feb 7 -74.44087 2181.1786 46.3222422 Mar 7 -76.37045 2254.6956 160.9648280 Apr 7 169.99975 2324.4035 8.4867699 May 7 160.38952 2394.1113 -39.1308576 Jun 7 97.98395 2455.3749 -107.6788423 Jul 7 73.58994 2516.6385 -99.1183933 Aug 7 -172.21489 2571.3601 292.1747741 Sep 7 -87.59234 2626.0818 113.3105491 Oct 7 -68.20202 2675.1410 -13.4489927 Nov 7 -58.64592 2724.2002 31.6756841 Dec 7 -24.17962 2771.8594 3.9502569 Jan 8 59.68293 2819.5185 -165.3014208 Feb 8 -74.44087 2829.7527 -8.1018242 Mar 8 -76.37045 2839.9869 218.7035414 Apr 8 169.99975 2819.3712 74.0190414 May 8 160.38952 2798.7555 99.5549721 Jun 8 97.98395 2770.3754 206.0206555 Jul 8 73.58994 2741.9953 525.4747727 Aug 8 -172.21489 2728.2977 943.9472215 Sep 8 -87.59234 2714.6001 -2234.1277222 Oct 8 -68.20202 2710.1125 429.6095076 Nov 8 -58.64592 2705.6250 -130.5690440 Dec 8 -24.17962 2720.2334 -345.3537877 Jan 9 59.68293 2734.8419 -305.8447818 Feb 9 -74.44087 2788.9099 158.1809515 Mar 9 -76.37045 2842.9780 453.6024539 Apr 9 169.99975 2929.9353 -21.8950091 May 9 160.38952 3016.8925 -133.3020413 Jun 9 97.98395 3093.2634 -56.9073011 Jul 9 73.58994 3169.6342 -101.3741272 Aug 9 -172.21489 3236.5181 63.7067864 Sep 9 -87.59234 3303.4020 25.3503076 Oct 9 -68.20202 3360.9906 96.6914313 Nov 9 -58.64592 3418.5791 46.4267735 Dec 9 -24.17962 3474.6414 -0.6218042 Jan 10 59.68293 3530.7037 15.8533677 Feb 10 -74.44087 3587.9063 140.5245398 Mar 10 -76.37045 3645.1090 38.5714810 Apr 10 169.99975 3702.5774 -160.0571635 May 10 160.38952 3760.0459 -116.9653773 Jun 10 97.98395 3805.3812 -97.0351131 Jul 10 73.58994 3850.7165 -155.9064151 Aug 10 -172.21489 3874.5931 249.6818177 Sep 10 -87.59234 3898.4697 323.9726582 Oct 10 -68.20202 3902.8290 226.2730557 Nov 10 -58.64592 3907.1882 151.3376718 Dec 10 -24.17962 3891.2240 136.9855854 Jan 11 59.68293 3875.2598 42.3972486 Feb 11 -74.44087 3829.9452 -105.4243058 Mar 11 -76.37045 3784.6305 0.5899089 Apr 11 169.99975 3714.8587 -120.0784567 May 11 160.38952 3645.0869 -43.6163915 Jun 11 97.98395 3569.8906 134.6754544 Jul 11 73.58994 3494.6943 205.2357341 Aug 11 -172.21489 3437.4278 163.4870776 Sep 11 -87.59234 3380.1613 -98.3589713 Oct 11 -68.20202 3342.2272 -178.4651746 Nov 11 -58.64592 3304.2931 -180.7971594 Dec 11 -24.17962 3278.2679 -231.1082492 Jan 12 59.68293 3252.2427 -424.2655894 Feb 12 -74.44087 3244.7942 8.5066628 Mar 12 -76.37045 3237.3458 277.4946842 Apr 12 169.99975 3248.6591 75.2111093 May 12 160.38952 3259.9725 1.5279651 Jun 12 97.98395 3272.4284 19.8676182 Jul 12 73.58994 3284.8844 -39.2342949 Aug 12 -172.21489 3290.4838 169.5710698 Sep 12 -87.59234 3296.0833 14.3290422 Oct 12 -68.20202 3292.1588 -41.2668017 Nov 12 -58.64592 3288.2343 -49.3784271 Dec 12 -24.17962 3280.0489 -139.5292963 Jan 13 59.68293 3271.8635 -34.0864161 Feb 13 -74.44087 3259.0635 172.8573651 Mar 13 -76.37045 3246.2635 216.1369153 Apr 13 169.99975 3233.8475 -84.3972223 May 13 160.38952 3221.4314 -18.2309291 Jun 13 97.98395 3209.6577 -4.1716759 Jul 13 73.58994 3197.8840 -60.9239890 Aug 13 -172.21489 3193.6213 28.8636068 Sep 13 -87.59234 3189.3585 -91.2161897 Oct 13 -68.20202 3195.7722 -115.9201660 Nov 13 -58.64592 3202.1858 -38.5599239 Dec 13 -24.17962 3222.2676 -110.2379489 Jan 14 59.68293 3242.3493 -141.8722243 Feb 14 -74.44087 3282.2434 111.4174591 Mar 14 -76.37045 3322.1375 186.7229116 Apr 14 169.99975 3379.5764 -73.8961196 May 14 160.38952 3437.0152 -249.9247200 Jun 14 97.98395 3503.7450 -212.9188996 Jul 14 73.58994 3570.4747 -33.8346454 Aug 14 -172.21489 3641.1643 222.5006419 Sep 14 -87.59234 3711.8538 -36.4014631 Oct 14 -68.20202 3775.1725 -2.3505192 Nov 14 -58.64592 3838.4913 18.9046433 Dec 14 -24.17962 3882.1301 98.5895664 Jan 15 59.68293 3925.7688 136.4882390 Feb 15 -74.44087 3946.1740 276.8268684 Mar 15 -76.37045 3966.5792 210.1612669 Apr 15 169.99975 3967.3387 -76.6284632 May 15 160.38952 3968.0982 19.3722375 Jun 15 97.98395 3947.1955 -118.5694012 Jul 15 73.58994 3926.2927 -134.4726061 Aug 15 -172.21489 3893.1187 257.6661786 Sep 15 -87.59234 3859.9448 79.5975708 Oct 15 -68.20202 3831.5864 -62.1643518 Nov 15 -58.64592 3803.2280 -5.9320559 Dec 15 -24.17962 3788.2447 2.8349098 Jan 16 59.68293 3773.2614 -121.9243751 Feb 16 -74.44087 3775.2164 -25.5555702 Mar 16 -76.37045 3777.1714 -140.2709962 Apr 16 169.99975 3796.8870 -243.0867663 May 16 160.38952 3816.6026 -62.7221056 Jun 16 97.98395 3823.6370 -50.8509210 Jul 16 73.58994 3830.6714 20.0986973 Aug 16 -172.21489 3748.8993 392.2055899 Sep 16 -87.59234 3667.1272 403.3950900 Oct 16 -68.20202 3592.7038 392.5882441 Nov 16 -58.64592 3518.2803 509.5456166 Dec 16 -24.17962 3519.1110 654.8786166 Jan 17 59.68293 3519.9417 827.2553662 Feb 17 -74.44087 3575.0122 -3076.7513576 Mar 17 -76.37045 3630.0828 -3135.9923123 Apr 17 169.99975 3725.8732 631.2870056 May 17 160.38952 3821.6637 635.3367544 Jun 17 97.98395 4003.2718 554.9742403 Jul 17 73.58994 4184.8799 321.4301601 Aug 17 -172.21489 4443.4088 381.2060848 Sep 17 -87.59234 4701.9377 108.6046172 Oct 17 -68.20202 4915.9420 -1.9299695 Nov 17 -58.64592 5129.9463 -96.0903377 Dec 17 -24.17962 5283.3833 -175.5636396 Jan 18 59.68293 5436.8203 -118.4631920 Feb 18 -74.44087 5595.8904 162.9904681 Mar 18 -76.37045 5754.9606 163.2798973 Apr 18 169.99975 5902.1325 -214.9022592 May 18 160.38952 6049.3045 -35.1739849 Jun 18 97.98395 6183.0138 132.1722442 Jul 18 73.58994 6316.7232 389.7969071 Aug 18 -172.21489 6467.6901 229.4648400 Sep 18 -87.59234 6618.6570 -64.3646195 Oct 18 -68.20202 6814.6954 -250.8833983 Nov 18 -58.64592 7010.7339 -552.5679586 Dec 18 -24.17962 7257.6649 -503.5052520 Jan 19 59.68293 7504.5959 -503.5087959 Feb 19 -74.44087 7756.9841 -259.2731789 Mar 19 -76.37045 8009.3722 136.1682072 Apr 19 169.99975 8224.4984 256.1818434 May 19 160.38952 8439.6246 338.0559104 Jun 19 97.98395 8622.1493 761.9467715 Jul 19 73.58994 8804.6740 1346.9960665 Aug 19 -172.21489 8942.6658 619.8190777 Sep 19 -87.59234 9080.6576 -446.9553035 Oct 19 -68.20202 9130.7304 -988.7584052 Nov 19 -58.64592 9180.8032 -466.8472885 Dec 19 -24.17962 9152.9003 21.3793516 Jan 20 59.68293 9124.9973 591.1297411 Feb 20 -74.44087 9082.7499 776.8310129 Mar 20 -76.37045 9040.5024 399.3080539 Apr 20 169.99975 9005.6175 128.5627207 May 20 160.38952 8970.7327 -100.8621818 Jun 20 97.98395 8888.0404 -65.2243312 Jul 20 73.58994 8805.3481 -272.8580468 Aug 20 -172.21489 8677.1839 -151.2190426 Sep 20 -87.59234 8549.0198 154.2025693 Oct 20 -68.20202 8428.6055 -231.7634375 Nov 20 -58.64592 8308.1911 466.3947742 Dec 20 -24.17962 8225.6333 299.3462975 Jan 21 59.68293 8143.0755 -60.1784296 Feb 21 -74.44087 8105.1158 -416.0149062 Mar 21 -76.37045 8067.1561 -431.8356137 Apr 21 169.99975 8058.4195 -407.6692828 May 21 160.38952 8049.6830 -381.1725211 Jun 21 97.98395 8058.6353 -252.0292210 Jul 21 73.58994 8067.5875 -0.2074871 Aug 21 -172.21489 8086.8659 568.3589856 Sep 21 -87.59234 8106.1443 304.1280659 Oct 21 -68.20202 8101.0784 235.1335861 Nov 21 -58.64592 8096.0126 364.6833248 Dec 21 -24.17962 8054.5768 147.3828591 Jan 22 59.68293 8013.1409 -122.2838571 Feb 22 -74.44087 7939.6194 184.7614679 Mar 22 -76.37045 7866.0979 -115.5974380 Apr 22 169.99975 7779.2675 -282.9072877 May 22 160.38952 7692.4372 -282.6467066 Jun 22 97.98395 7621.8332 -25.3671255 Jul 22 73.58994 7551.2292 185.8208892 Aug 22 -172.21489 7517.7419 402.9030426 Sep 22 -87.59234 7484.2545 -356.0221964 Oct 22 -68.20202 7473.0535 -327.5914883 Nov 22 -58.64592 7461.8525 -157.6965618 Dec 22 -24.17962 7425.2488 -111.9492224 Jan 23 59.68293 7388.6452 38.5918665 Feb 23 -74.44087 7303.9377 290.3832227 Mar 23 -76.37045 7219.2301 411.9803480 Apr 23 169.99975 7097.1710 513.7192467 May 23 160.38952 6975.1119 612.5885763 Jun 23 97.98395 6812.2568 242.0092423 Jul 23 73.58994 6649.4017 -238.3316579 Aug 23 -172.21489 6446.5563 -19.7614093 Sep 23 -87.59234 6243.7109 -288.7985531 Oct 23 -68.20202 6047.3570 -434.9949593 Nov 23 -58.64592 5851.0031 30.3828531 Dec 23 -24.17962 5726.5387 -11.7290726 Jan 24 59.68293 5602.0743 -96.9772489 Feb 24 -74.44087 5571.4604 -408.6295141 Mar 24 -76.37045 5540.8465 -680.2560103 Apr 24 169.99975 5577.1301 -414.6698665 May 24 160.38952 5613.4138 -232.3232918 Jun 24 97.98395 5704.9533 -79.0172271 Jul 24 73.58994 5796.4928 -133.0927285 Aug 24 -172.21489 5943.9103 220.3746264 Sep 24 -87.59234 6091.3277 87.6945890 Oct 24 -68.20202 6250.1807 -23.8087080 Nov 24 -58.64592 6409.0337 -46.5977864 Dec 24 -24.17962 6542.0860 -168.1963622 Jan 25 59.68293 6675.1383 68.1388115 Feb 25 -74.44087 6801.0612 406.0596584 Mar 25 -76.37045 6926.9842 222.6762744 Apr 25 169.99975 7072.5454 21.9547990 May 25 160.38952 7218.1067 -273.1662457 Jun 25 97.98395 7385.3694 -264.6433914 Jul 25 73.58994 7552.6322 -400.5021033 Aug 25 -172.21489 7737.6322 -211.1673130 Sep 25 -87.59234 7922.6323 -89.5799152 Oct 25 -68.20202 8118.8824 19.5796542 Nov 25 -58.64592 8315.1325 109.8434420 Dec 25 -24.17962 8511.4651 180.2245562 Jan 26 59.68293 8707.7977 86.8594200 Feb 26 -74.44087 8896.6024 395.9384309 Mar 26 -76.37045 9085.4072 323.8632110 Apr 26 169.99975 9260.5905 -72.2802287 May 26 160.38952 9435.7737 -347.5032376 Jun 26 97.98395 9613.6347 -310.4186754 Jul 26 73.58994 9791.4957 -213.0456794 Aug 26 -172.21489 10002.0362 127.5586797 Sep 26 -87.59234 10212.5767 -14.3543536 Oct 26 -68.20202 10435.6520 -198.1899622 Nov 26 -58.64592 10658.7273 -256.3013523 Dec 26 -24.17962 10846.9446 -72.5549646 Jan 27 59.68293 11035.1619 242.6551726 Feb 27 -74.44087 11199.7931 661.6077656 Mar 27 -76.37045 11364.4243 794.9861276 Apr 27 169.99975 11539.5619 298.1783487 May 27 160.38952 11714.6995 -129.1589994 Jun 27 97.98395 11894.2418 -940.7157052 Jul 27 73.58994 12073.7840 -701.4739772 Aug 27 -172.21489 12254.0466 -156.9516694 Sep 27 -87.59234 12434.3091 -99.0867539 Oct 27 -68.20202 12647.7045 111.4075328 Nov 27 -58.64592 12861.0999 108.2460381 Dec 27 -24.17962 13084.5162 141.7833919 Jan 28 59.68293 13307.9326 287.0544951 Feb 28 -74.44087 13459.1223 478.1385323 Mar 28 -76.37045 13610.3121 -10.0116614 Apr 28 169.99975 13664.1776 376.9926111 May 28 160.38952 13718.0432 631.9173143 Jun 28 97.98395 13669.6139 521.6321887 Jul 28 73.58994 13621.1846 417.0454968 Aug 28 -172.21489 13474.5091 -215.7042552 Sep 28 -87.59234 13327.8337 111.2986003 Oct 28 -68.20202 13123.8020 692.0900509 Nov 28 -58.64592 12919.7702 -5.5142800 Dec 28 -24.17962 12661.5454 289.5641809 Jan 29 59.68293 12403.3207 -341.0536087 Feb 29 -74.44087 12074.5521 -268.4611906 Mar 29 -76.37045 11745.7835 -29.9030035 Apr 29 169.99975 11305.4997 688.2805744 May 29 160.38952 10865.2159 1003.9245830 Jun 29 97.98395 10347.8841 788.3119877 Jul 29 73.58994 9830.5522 -52.0121737 Aug 29 -172.21489 9289.1787 592.0761995 Sep 29 -87.59234 8747.8052 672.5371804 Oct 29 -68.20202 8240.9289 -1064.1269032 Nov 29 -58.64592 7734.0527 -983.9167683 Dec 29 -24.17962 7352.4599 -1185.2303078 Jan 30 59.68293 6970.8672 -651.4000978 Feb 30 -74.44087 6798.5689 -729.5479872 Mar 30 -76.37045 6626.2706 -941.9601075 Apr 30 169.99975 6660.5108 -784.3805943 May 30 160.38952 6694.7511 -230.1806504 Jun 30 97.98395 6856.4296 -301.8735478 Jul 30 73.58994 7018.1081 -395.6980114 Aug 30 -172.21489 7215.1624 272.2125219 Sep 30 -87.59234 7412.2167 583.1656628 Oct 30 -68.20202 7588.9067 545.6452751 Nov 30 -58.64592 7765.5968 232.6891060 Dec 30 -24.17962 7877.6695 214.9901209 Jan 31 59.68293 7989.7422 136.9048853 Feb 31 -74.44087 8051.1649 -1.5140430 Mar 31 -76.37045 8112.5876 321.2927977 Apr 31 169.99975 8158.8802 134.5000668 May 31 160.38952 8205.1727 -427.8822334 Jun 31 97.98395 8257.3899 -320.7538660 Jul 31 73.58994 8309.6071 -326.5870648 Aug 31 -172.21489 8363.9073 -14.7423973 Sep 31 -87.59234 8418.2075 110.4248779 Oct 31 -68.20202 8467.5199 298.0720987 Nov 31 -58.64592 8516.8324 207.3835380 Dec 31 -24.17962 8486.9489 163.0007531 Jan 32 59.68293 8457.0654 201.6717176 Feb 32 -74.44087 8268.2794 628.5014940 Mar 32 -76.37045 8079.4934 594.5470395 Apr 32 169.99975 7870.2856 741.7646180 May 32 160.38952 7661.0779 839.5926273 Jun 32 97.98395 7516.0029 651.3331114 Jul 32 73.58994 7370.9280 628.0620293 Aug 32 -172.21489 7212.1787 -6318.1137680 Sep 32 -87.59234 7053.4293 172.7630422 Oct 32 -68.20202 6890.8773 528.4347312 Nov 32 -58.64592 6728.3253 407.3206388 Dec 32 -24.17962 6581.6300 714.9196483 Jan 33 59.68293 6434.9347 1083.2224073 > m$win s t l 3851 19 13 > m$deg s t l 0 1 1 > m$jump s t l 386 2 2 > m$inner [1] 2 > m$outer [1] 0 > postscript(file="/var/wessaorg/rcomp/tmp/1t9js1355691180.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m,main=main) > dev.off() null device 1 > mylagmax <- nx/2 > postscript(file="/var/wessaorg/rcomp/tmp/2a53h1355691180.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > acf(as.numeric(x),lag.max = mylagmax,main='Observed') > acf(as.numeric(m$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/wessaorg/rcomp/tmp/3rbsq1355691180.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/wessaorg/rcomp/tmp/4847c1355691180.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/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,'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$jump['l']) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/5zdsv1355691180.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Seasonal',header=TRUE) > a<-table.element(a,'Trend',header=TRUE) > a<-table.element(a,'Remainder',header=TRUE) > a<-table.row.end(a) > for (i in 1:nx) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]+m$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/wessaorg/rcomp/tmp/6pj271355691180.tab") > > try(system("convert tmp/1t9js1355691180.ps tmp/1t9js1355691180.png",intern=TRUE)) character(0) > try(system("convert tmp/2a53h1355691180.ps tmp/2a53h1355691180.png",intern=TRUE)) character(0) > try(system("convert tmp/3rbsq1355691180.ps tmp/3rbsq1355691180.png",intern=TRUE)) character(0) > try(system("convert tmp/4847c1355691180.ps tmp/4847c1355691180.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 7.152 0.438 7.576