R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(1483509
+ ,8036554
+ ,4623093
+ ,5528662
+ ,4221032
+ ,8061847
+ ,7640066
+ ,2935533
+ ,8161548
+ ,2543967
+ ,13163450
+ ,3348436
+ ,3997440
+ ,2322911
+ ,2019457
+ ,3047748
+ ,5728767
+ ,2605173
+ ,5646743
+ ,13121544
+ ,3453409
+ ,1878333
+ ,4247362
+ ,23022552
+ ,7646203
+ ,9016602
+ ,3606568
+ ,3173510
+ ,17568772
+ ,10805045
+ ,31056269
+ ,15623385
+ ,6663443
+ ,35435745
+ ,2823250
+ ,5197089
+ ,4120632
+ ,8832767
+ ,3695374
+ ,8385805
+ ,3777904
+ ,5199532
+ ,5297275
+ ,14847382
+ ,5900158
+ ,4416718
+ ,3926429
+ ,4876884
+ ,2795297
+ ,3385527
+ ,3877941
+ ,3556729
+ ,4982836
+ ,2976325
+ ,2295026
+ ,2218752
+ ,4146062
+ ,3302091
+ ,3864505
+ ,5454794
+ ,1749836
+ ,6684048
+ ,2809918
+ ,4092664
+ ,5070470
+ ,9814477
+ ,6665318
+ ,3912554
+ ,6188129
+ ,3627991
+ ,3308767
+ ,3820332
+ ,4932979
+ ,5567917
+ ,5020814
+ ,3803273
+ ,3999984
+ ,4883104
+ ,13731747
+ ,47531824
+ ,8415570
+ ,22178158
+ ,61211654
+ ,18223748
+ ,17678085
+ ,49299580
+ ,25899948
+ ,34121754
+ ,9859231
+ ,29740892
+ ,21085212
+ ,43003866
+ ,59549247
+ ,18026465
+ ,4680597
+ ,5564728
+ ,11792347
+ ,10371624
+ ,3728446
+ ,5732978
+ ,4067638
+ ,2395508
+ ,5018801
+ ,22068888
+ ,7678580
+ ,15510095
+ ,6471239
+ ,14349204
+ ,35151574
+ ,8210488
+ ,5022664
+ ,13996871
+ ,12822431
+ ,14011552
+ ,20260980
+ ,23718976
+ ,45833049
+ ,30688420
+ ,16576062
+ ,14844405
+ ,16728286
+ ,43477680
+ ,57497427
+ ,24233726
+ ,24921208
+ ,9516725
+ ,27977239
+ ,21632046
+ ,22956809
+ ,9704324
+ ,19871149
+ ,5553842
+ ,5667858
+ ,4348188
+ ,10025042
+ ,10639796
+ ,8639184
+ ,10764378
+ ,12097733
+ ,3988414
+ ,4607102
+ ,7126895
+ ,6009625
+ ,21533237
+ ,5986771
+ ,5455310
+ ,1822874
+ ,3374062
+ ,2920748
+ ,2295942
+ ,6809829
+ ,3318281
+ ,13784645
+ ,7366577
+ ,1628637
+ ,4258976
+ ,7159779
+ ,8098401
+ ,6894240
+ ,3771246
+ ,3249726
+ ,3147380
+ ,4063037
+ ,9621916
+ ,5890158
+ ,2142901
+ ,3145007
+ ,1562168
+ ,3303103
+ ,5886910
+ ,3454270
+ ,6995348
+ ,6487869
+ ,12091976
+ ,3934625
+ ,3999749
+ ,3613526
+ ,4271706
+ ,4253390
+ ,5551591
+ ,4663041
+ ,2104104
+ ,5385399
+ ,6205877
+ ,7529500
+ ,17222705
+ ,6230913
+ ,6508275
+ ,4518884
+ ,4234991
+ ,5625388
+ ,5810139
+ ,6942187
+ ,3711188
+ ,4261281
+ ,1989945
+ ,5033342
+ ,7239565
+ ,11058795
+ ,7384772
+ ,3884771
+ ,3239201
+ ,2316403
+ ,4034947
+ ,3245271
+ ,2387251
+ ,2174886
+ ,3436080
+ ,3738956
+ ,1884730
+ ,1509144
+ ,42728366
+ ,3446317
+ ,4600683
+ ,2953615
+ ,3570060
+ ,2130208
+ ,2442943
+ ,4892020
+ ,3222192
+ ,3121617
+ ,3665542
+ ,5519432
+ ,4113468
+ ,1714614
+ ,3651985
+ ,2419548
+ ,2378854
+ ,2303949
+ ,2555534
+ ,1713005
+ ,1705960
+ ,6115046
+ ,3951044
+ ,3785568
+ ,4670530
+ ,2265100
+ ,1105643
+ ,2814152
+ ,3728673
+ ,2038949
+ ,2402919
+ ,2348814
+ ,2797822
+ ,902505
+ ,1331319
+ ,4204238
+ ,2212485
+ ,6797382
+ ,4532324
+ ,1778808
+ ,1890720
+ ,5463736
+ ,11368931
+ ,2040164
+ ,4276399
+ ,3714445
+ ,2068168
+ ,1003842
+ ,2858535
+ ,2355484
+ ,2719262
+ ,1897741
+ ,3945185
+ ,3799916
+ ,1017654
+ ,3052241
+ ,3932970
+ ,3598151
+ ,2296005
+ ,2202018
+ ,2461777
+ ,2452042
+ ,2185142
+ ,11968502
+ ,20395972
+ ,21756900
+ ,30024300
+ ,10811344
+ ,1819202
+ ,1276885
+ ,2946701
+ ,3587459
+ ,2832691
+ ,6674805
+ ,3868362
+ ,4302909
+ ,23265229
+ ,22348002
+ ,11883953
+ ,6634979
+ ,2935493
+ ,3425669
+ ,1171611
+ ,6875879
+ ,19451908
+ ,13885933
+ ,7643317
+ ,10797966
+ ,7297445
+ ,8739736
+ ,12455537
+ ,24291181
+ ,4215150
+ ,28652176
+ ,6851172
+ ,3746871
+ ,7327861
+ ,16829710
+ ,13778594
+ ,6463717
+ ,8956867
+ ,21204915
+ ,16115855
+ ,2536113
+ ,16645717
+ ,17003730
+ ,15969006
+ ,31020427
+ ,23798897
+ ,20770321
+ ,44410402
+ ,27037491
+ ,29627771
+ ,18189792
+ ,4654610
+ ,12307201
+ ,15300578
+ ,10623864
+ ,6880178
+ ,29947357
+ ,18611399
+ ,42432604
+ ,20208278
+ ,14004392
+ ,25737765
+ ,16735738
+ ,22450825
+ ,6880840
+ ,8510379
+ ,8182481
+ ,10948683
+ ,4805277
+ ,2589229
+ ,5658407
+ ,12862611
+ ,5666188
+ ,6875556
+ ,7098766
+ ,36083309
+ ,10200330
+ ,7784976)
> 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  -281874.9  5803973  -4038588.919
Feb  1  1826059.3  5783442    427052.786
Mar  1 -1563471.0  5762911    423652.927
Apr  1 -2268240.5  5726155   2070747.024
May  1 -1814951.5  5689400    346583.722
Jun  1 -2126389.1  5652816   4535420.404
Jul  1   487710.9  5616232   1536123.619
Aug  1  3543437.4  5552342  -6160246.579
Sep  1  2165306.6  5488453    507788.489
Oct  1   654822.7  5274408  -3385263.290
Nov  1  -813125.4  5060362   8916213.075
Dec  1   190715.6  4996920  -1839199.594
Jan  2  -281874.9  4933478   -654162.707
Feb  2  1826059.3  4956171  -4459319.625
Mar  2 -1563471.0  4978865  -1395937.107
Apr  2 -2268240.5  5004726    311262.026
May  2 -1814951.5  5030588   2513130.759
Jun  2 -2126389.1  5391873   -660310.944
Jul  2   487710.9  5753158   -594126.116
Aug  2  3543437.4  6235167   3342939.565
Sep  2  2165306.6  6717176  -5429073.489
Oct  2   654822.7  7176533  -5953022.478
Nov  2  -813125.4  7635890  -2575402.325
Dec  2   190715.6  8495583  14336253.530
Jan  3  -281874.9  9355276  -1427198.060
Feb  3  1826059.3 10417184  -3226641.337
Mar  3 -1563471.0 11479092  -6309053.179
Apr  3 -2268240.5 12257643  -6815892.948
May  3 -1814951.5 13036195   6347528.883
Jun  3 -2126389.1 13100963   -169528.729
Jul  3   487710.9 13165731  17402827.191
Aug  3  3543437.4 12922420   -842472.681
Sep  3  2165306.6 12679110  -8180973.287
Oct  3   654822.7 12119142  22661780.689
Nov  3  -813125.4 11559174  -7922798.192
Dec  3   190715.6 10617691  -5611317.516
Jan  4  -281874.9  9676208  -5273701.285
Feb  4  1826059.3  8789362  -1782654.311
Mar  4 -1563471.0  7902516  -2643670.901
Apr  4 -2268240.5  7298958   3355087.733
May  4 -1814951.5  6695400  -1102544.033
Jun  4 -2126389.1  6387605    938316.397
Jul  4   487710.9  6079810  -1270245.641
Aug  4  3543437.4  5832076   5471868.334
Sep  4  2165306.6  5584343  -1849491.426
Oct  4   654822.7  5352643  -1590748.095
Nov  4  -813125.4  5120944   -381389.622
Dec  4   190715.6  4885530   -199361.515
Jan  5  -281874.9  4650116  -1572943.854
Feb  5  1826059.3  4329830  -2770361.793
Mar  5 -1563471.0  4009543   1431868.702
Apr  5 -2268240.5  3814060   2010909.464
May  5 -1814951.5  3618577   3179210.827
Jun  5 -2126389.1  3567712   1535001.570
Jul  5   487710.9  3516848  -1709533.155
Aug  5  3543437.4  3509090  -4833774.858
Sep  5  2165306.6  3501331  -1520575.297
Oct  5   654822.7  3599809   -952540.976
Nov  5  -813125.4  3698288    979342.488
Dec  5   190715.6  4036445   1227633.677
Jan  6  -281874.9  4374601  -2342890.578
Feb  6  1826059.3  4683016    174973.045
Mar  6 -1563471.0  4991430   -618040.898
Apr  6 -2268240.5  5062048   1298856.632
May  6 -1814951.5  5132666   1752755.762
Jun  6 -2126389.1  5099265   6841601.141
Jul  6   487710.9  5065864   1111743.053
Aug  6  3543437.4  5019682  -4650565.627
Sep  6  2165306.6  4973500   -950678.042
Oct  6   654822.7  4892574  -1919405.817
Nov  6  -813125.4  4811648   -689755.449
Dec  6   190715.6  5193743  -1564126.484
Jan  7  -281874.9  5575838   -360983.964
Feb  7  1826059.3  6870978  -3129120.272
Mar  7 -1563471.0  8166118  -1581833.145
Apr  7 -2268240.5 10343516  -4272002.155
May  7 -1814951.5 12520913  -6705977.563
Jun  7 -2126389.1 14964616  -7955122.956
Jul  7   487710.9 17408319  -4164282.816
Aug  7  3543437.4 19911327  24077059.564
Sep  7  2165306.6 22414335 -16164071.792
Oct  7   654822.7 24387367  -2864031.587
Nov  7  -813125.4 26360399  35664380.762
Dec  7   190715.6 27515215  -9482183.138
Jan  8  -281874.9 28670032 -10710072.482
Feb  8  1826059.3 29380369  18093151.602
Mar  8 -1563471.0 30090706  -2627286.879
Apr  8 -2268240.5 29885147   6504847.134
May  8 -1814951.5 29679589 -18005406.253
Jun  8 -2126389.1 28172223   3695058.391
Jul  8   487710.9 26664857  -6067355.434
Aug  8  3543437.4 24678831  14781597.746
Sep  8  2165306.6 22692805  34691135.191
Oct  8   654822.7 20639518  -3267875.642
Nov  8  -813125.4 18586231 -13092508.332
Dec  8   190715.6 16434751 -11060738.307
Jan  9  -281874.9 14283271  -2209048.726
Feb  9  1826059.3 12265212  -3719647.726
Mar  9 -1563471.0 10247154  -4955237.290
Apr  9 -2268240.5  9370786  -1369567.457
May  9 -1814951.5  8494418  -2611828.024
Jun  9 -2126389.1  9047917  -4526019.608
Jul  9   487710.9  9601416  -5070325.659
Aug  9  3543437.4 10318752   8206699.060
Sep  9  2165306.6 11036087  -5522813.955
Oct  9   654822.7 11744385   3110887.460
Nov  9  -813125.4 12452682  -5168317.982
Dec  9   190715.6 13214142    944345.887
Jan 10  -281874.9 13975603  21457846.310
Feb 10  1826059.3 15150404  -8765975.252
Mar 10 -1563471.0 16325205  -9739070.379
Apr 10 -2268240.5 17518308  -1253196.139
May 10 -1814951.5 18711410  -4074027.299
Jun 10 -2126389.1 19541256  -3403314.591
Jul 10   487710.9 20371101   -597832.350
Aug 10  3543437.4 21874651  -1699112.233
Sep 10  2165306.6 23378200  20289542.149
Oct 10   654822.7 25100545   4933052.584
Nov 10  -813125.4 26822889  -9433701.837
Dec 10   190715.6 27408437 -12754747.847
Jan 11  -281874.9 27993985 -10983824.301
Feb 11  1826059.3 27537409  14114211.893
Mar 11 -1563471.0 27080832  31980065.522
Apr 11 -2268240.5 26205462    296504.834
May 11 -1814951.5 25330091   1406068.747
Jun 11 -2126389.1 23870817 -12227702.892
Jul 11   487710.9 22411543   5077985.002
Aug 11  3543437.4 20057141  -1968532.353
Sep 11  2165306.6 17702739   3088763.556
Oct 11   654822.7 15745915  -6696413.994
Nov 11  -813125.4 13789092   6895182.599
Dec 11   190715.6 12759180  -7396053.598
Jan 12  -281874.9 11729268  -5779535.241
Feb 12  1826059.3 10746418  -8224289.449
Mar 12 -1563471.0  9763568   1824944.778
Apr 12 -2268240.5  9161818   3746218.705
May 12 -1814951.5  8560067   1894068.233
Jun 12 -2126389.1  8526327   4364440.169
Jul 12   487710.9  8492586   3117435.637
Aug 12  3543437.4  8401113  -7956136.215
Sep 12  2165306.6  8309639  -5867843.802
Oct 12   654822.7  7844295  -1372222.400
Nov 12  -813125.4  7378950   -556199.855
Dec 12   190715.6  6990534  14351987.809
Jan 13  -281874.9  6602117   -333470.971
Feb 13  1826059.3  6476172  -2846921.194
Mar 13 -1563471.0  6350227  -2963881.982
Apr 13 -2268240.5  6141041   -498738.346
May 13 -1814951.5  5931855  -1196155.110
Jun 13 -2126389.1  5627434  -1205102.658
Jul 13   487710.9  5323013    999105.327
Aug 13  3543437.4  5350996  -5576152.627
Sep 13  2165306.6  5378980   6240358.684
Oct 13   654822.7  5541489   1170264.853
Nov 13  -813125.4  5703999  -3262236.834
Dec 13   190715.6  5753508  -1685247.444
Jan 14  -281874.9  5803016   1638637.501
Feb 14  1826059.3  5724777    547565.207
Mar 14 -1563471.0  5646537   2811174.348
Apr 14 -2268240.5  5438240    601246.775
May 14 -1814951.5  5229943   -165265.198
Jun 14 -2126389.1  4973341    300428.120
Jul 14   487710.9  4716739  -1141413.029
Aug 14  3543437.4  4480831   1597647.841
Sep 14  2165306.6  4244922   -520071.024
Oct 14   654822.7  4316553  -2828474.687
Nov 14  -813125.4  4388184   -430051.207
Dec 14   190715.6  4662816  -3291363.524
Jan 15  -281874.9  4937448  -1352470.285
Feb 15  1826059.3  5056663   -995812.356
Mar 15 -1563471.0  5175878   -158136.991
Apr 15 -2268240.5  5226433   4037155.754
May 15 -1814951.5  5276987   3025833.099
Jun 15 -2126389.1  5303677   8914687.916
Jul 15   487710.9  5330367  -1883452.735
Aug 15  3543437.4  5213426  -4757114.267
Sep 15  2165306.6  5096485  -3648265.534
Oct 15   654822.7  5060372  -1443488.387
Nov 15  -813125.4  5024258     42256.903
Dec 15   190715.6  5319322     41552.882
Jan 16  -281874.9  5614386   -669470.583
Feb 16  1826059.3  5960753  -5682708.407
Mar 16 -1563471.0  6307120    641750.204
Apr 16 -2268240.5  6440332   2033785.084
May 16 -1814951.5  6573545   2770906.564
Jun 16 -2126389.1  6607337  12741756.785
Jul 16   487710.9  6641130   -897927.462
Aug 16  3543437.4  6530259  -3565421.149
Sep 16  2165306.6  6419388  -4065810.570
Oct 16   654822.7  6097780  -2517612.076
Nov 16  -813125.4  5776173    662340.562
Dec 16   190715.6  5623546     -4123.074
Jan 17  -281874.9  5470920   1753141.844
Feb 17  1826059.3  5546257  -3661127.786
Mar 17 -1563471.0  5621593    203159.020
Apr 17 -2268240.5  5568313  -1310127.948
May 17 -1814951.5  5515034   1333259.685
Jun 17 -2126389.1  5307295   4058659.112
Jul 17   487710.9  5099556   5471528.070
Aug 17  3543437.4  4882140  -1040805.565
Sep 17  2165306.6  4664724  -2945259.935
Oct 17   654822.7  4430428  -1846049.674
Nov 17  -813125.4  4196132  -1066603.269
Dec 17   190715.6  4182056   -337824.252
Jan 18  -281874.9  4167980   -640833.681
Feb 18  1826059.3  4737191  -4175999.737
Mar 18 -1563471.0  5306403  -1568046.359
Apr 18 -2268240.5  5860339   -156018.672
May 18 -1814951.5  6414275   -860367.384
Jun 18 -2126389.1  6576966  -2565847.292
Jul 18   487710.9  6739658  -5718224.668
Aug 18  3543437.4  6719960  32464968.778
Sep 18  2165306.6  6700262  -5419251.511
Oct 18   654822.7  6559453  -2613592.912
Nov 18  -813125.4  6418645  -2651904.169
Dec 18   190715.6  5990553  -2611208.829
Jan 19  -281874.9  5562462  -3150378.934
Feb 19  1826059.3  4881467  -4264583.682
Mar 19 -1563471.0  4200473   2255018.005
Apr 19 -2268240.5  3872366   1618066.886
May 19 -1814951.5  3544258   1392310.368
Jun 19 -2126389.1  3441535   2350396.547
Jul 19   487710.9  3338811   1692910.257
Aug 19  3543437.4  3196857  -2626826.485
Sep 19  2165306.6  3054903  -3505595.963
Oct 19   654822.7  2964918     32244.483
Nov 19  -813125.4  2874932    357741.072
Dec 19   190715.6  2951389   -763250.838
Jan 20  -281874.9  3027846   -442022.194
Feb 20  1826059.3  3101828  -2372353.284
Mar 20 -1563471.0  3175810    100666.061
Apr 20 -2268240.5  3167764    806436.725
May 20 -1814951.5  3159718   4770279.989
Jun 20 -2126389.1  3124233   2953199.680
Jul 20   487710.9  3088749    209107.902
Aug 20  3543437.4  3024565  -1897471.995
Sep 20  2165306.6  2960380  -2860586.626
Oct 20   654822.7  2837489  -2386668.319
Nov 20  -813125.4  2714597    912680.132
Dec 20   190715.6  2647072    890885.381
Jan 21  -281874.9  2579547   -258722.815
Feb 21  1826059.3  2647172  -2070312.724
Mar 21 -1563471.0  2714798   1197486.802
Apr 21 -2268240.5  2800020   2266042.292
May 21 -1814951.5  2885242   -167785.616
Jun 21 -2126389.1  2984011    473697.116
Jul 21   487710.9  3082780    633747.380
Aug 21  3543437.4  3293372  -4624324.751
Sep 21  2165306.6  3503965   1128110.383
Oct 21   654822.7  3726570    150931.689
Nov 21  -813125.4  3949174  -1357240.862
Dec 21   190715.6  4065255  -2365250.444
Jan 22  -281874.9  4181335   1564275.531
Feb 22  1826059.3  4103682   5439189.416
Mar 22 -1563471.0  4026029   -422394.264
Apr 22 -2268240.5  3836246   2708393.310
May 22 -1814951.5  3646463   1882933.484
Jun 22 -2126389.1  3423614    770943.196
Jul 22   487710.9  3200765  -2684633.560
Aug 22  3543437.4  2936840  -3621741.994
Sep 22  2165306.6  2672915  -2482737.162
Oct 22   654822.7  2618038   -553599.121
Nov 22  -813125.4  2563162    147704.064
Dec 22   190715.6  2686136   1068333.231
Jan 23  -281874.9  2809110   1272680.953
Feb 23  1826059.3  2894453  -3702858.458
Mar 23 -1563471.0  2979796   1635915.565
Apr 23 -2268240.5  3220218   2980991.998
May 23 -1814951.5  3460641   1952462.032
Jun 23 -2126389.1  4415963      6430.891
Jul 23   487710.9  5371286  -3656978.719
Aug 23  3543437.4  6706281  -7787941.852
Sep 23  2165306.6  8041277  -7754541.721
Oct 23   654822.7  8851056  -7320737.099
Nov 23  -813125.4  9660836   3120791.666
Dec 23   190715.6  9963587  10241669.417
Jan 24  -281874.9 10266338  11772436.724
Feb 24  1826059.3 10226955  17971285.572
Mar 24 -1563471.0 10187572   2187242.856
Apr 24 -2268240.5  9688008  -5600565.917
May 24 -1814951.5  9188445  -6096608.088
Jun 24 -2126389.1  8644595  -3571504.662
Jul 24   487710.9  8100745  -5000996.703
Aug 24  3543437.4  7915149  -8625895.255
Sep 24  2165306.6  7729553  -3220054.541
Oct 24   654822.7  7936587  -4723047.279
Nov 24  -813125.4  8143620  -3027585.874
Dec 24   190715.6  8474552  14599961.600
Jan 25  -281874.9  8805483  13824393.628
Feb 25  1826059.3  9227298    830595.372
Mar 25 -1563471.0  9649113  -1450663.450
Apr 25 -2268240.5  9716469  -4512735.716
May 25 -1814951.5  9783825  -4543204.381
Jun 25 -2126389.1  9426847  -6128846.440
Jul 25   487710.9  9069868  -2681699.966
Aug 25  3543437.4  9181271   6727199.856
Sep 25  2165306.6  9292673   2427952.943
Oct 25   654822.7 10133749  -3145254.217
Nov 25  -813125.4 10974824    636267.766
Dec 25   190715.6 11540150  -4433420.328
Jan 26  -281874.9 12105476  -3083864.867
Feb 26  1826059.3 12137438  -1507960.511
Mar 26 -1563471.0 12169401  13685251.280
Apr 26 -2268240.5 12142583  -5659192.134
May 26 -1814951.5 12115764  18351363.053
Jun 26 -2126389.1 12180964  -3203402.587
Jul 26   487710.9 12246163  -8987002.696
Aug 26  3543437.4 12092952  -8308528.359
Sep 26  2165306.6 11939741   2724662.242
Oct 26   654822.7 11920544   1203227.800
Nov 26  -813125.4 11901346  -4624503.499
Dec 26   190715.6 12639797  -3873645.235
Jan 27  -281874.9 13378247   8108542.583
Feb 27  1826059.3 14721055   -431259.519
Mar 27 -1563471.0 16063863 -11964279.187
Apr 27 -2268240.5 17622384   1291573.328
May 27 -1814951.5 19180905   -362223.556
Jun 27 -2126389.1 20450842  -2355447.370
Jul 27   487710.9 21720780   8811936.348
Aug 27  3543437.4 22086611  -1831150.976
Sep 27  2165306.6 22452441  -3847427.036
Oct 27   654822.7 22130720  21624859.588
Nov 27  -813125.4 21808998   6041618.355
Dec 27   190715.6 21145771   8291284.544
Jan 28  -281874.9 20482544  -2010876.711
Feb 28  1826059.3 19986841 -17158290.253
Mar 28 -1563471.0 19491138  -5620466.359
Apr 28 -2268240.5 19124137  -1555318.392
May 28 -1814951.5 18757135  -6318319.825
Jun 28 -2126389.1 18799992  -9793424.471
Jul 28   487710.9 18842848  10616798.416
Aug 28  3543437.4 19170326  -4102364.091
Sep 28  2165306.6 19497804  20769493.668
Oct 28   654822.7 19345623    207832.356
Nov 28  -813125.4 19193442  -4375924.812
Dec 28   190715.6 18244797   7302251.916
Jan 29  -281874.9 17296153   -278539.802
Feb 29  1826059.3 15642506   4982259.497
Mar 29 -1563471.0 13988860  -5544548.769
Apr 29 -2268240.5 12432833  -1654213.170
May 29 -1814951.5 10876806   -879372.970
Jun 29 -2126389.1  9994770   3080301.648
Jul 29   487710.9  9112735  -4795169.202
Aug 29  3543437.4  9555053 -10509260.964
Sep 29  2165306.6  9997370  -6504269.460
Oct 29   654822.7 10369568   1838220.016
Nov 29  -813125.4 10741767  -4262453.365
Dec 29   190715.6 11200555  -4515714.708
Jan 30  -281874.9 11659343  -4278702.495
Feb 30  1826059.3 12268904  21988346.148
Mar 30 -1563471.0 12878464  -1114662.773
Apr 30 -2268240.5 13593443  -3540226.912
> m$win
   s    t    l 
3521   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
353   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/11jm71322665187.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/wessaorg/rcomp/tmp/27wkk1322665187.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$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/3gx5n1322665187.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/45lxm1322665187.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$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5zmgn1322665187.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$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/64kyg1322665187.tab") 
> 
> try(system("convert tmp/11jm71322665187.ps tmp/11jm71322665187.png",intern=TRUE))
character(0)
> try(system("convert tmp/27wkk1322665187.ps tmp/27wkk1322665187.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gx5n1322665187.ps tmp/3gx5n1322665187.png",intern=TRUE))
character(0)
> try(system("convert tmp/45lxm1322665187.ps tmp/45lxm1322665187.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.545   0.255   4.833