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)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '1'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> 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  45.99808 209.0885 -19.9865607
Feb  1  54.85858 212.7529  13.0885624
Mar  1  31.55457 216.4172  16.6281920
Apr  1  -8.36346 220.4957  28.5678036
May  1 -29.89762 224.5741   6.7235462
Jun  1  41.95136 229.1315 -30.2828598
Jul  1  16.43189 233.6889  -9.0208094
Aug  1 -15.16009 238.4350   0.5251215
Sep  1 -33.48874 243.1810  -3.5922727
Oct  1 -49.26018 250.2608 -26.3006344
Nov  1 -27.95495 257.3406 -26.0856595
Dec  1 -26.66943 270.4473 -23.2778386
Jan  2  45.99808 283.5539 -30.0519922
Feb  2  54.85858 299.1759  -6.6344382
Mar  2  31.55457 314.7978  -8.0523777
Apr  2  -8.36346 330.4529   5.6105814
May  2 -29.89762 346.1080  35.3896714
Jun  2  41.95136 359.6710  -5.0223228
Jul  2  16.43189 373.2340  49.1341394
Aug  2 -15.16009 382.7155  28.0446330
Sep  2 -33.48874 392.1969   4.7918013
Oct  2 -49.26018 395.2833  32.7768765
Nov  2 -27.95495 398.3697 -13.4147119
Dec  2 -26.66943 394.2496   1.4197960
Jan  3  45.99808 390.1296  28.6723295
Feb  3  54.85858 380.5737  43.6676787
Mar  3  31.55457 371.0179  28.7275343
Apr  3  -8.36346 358.6505  16.2129557
May  3 -29.89762 346.2831   9.9145081
Jun  3  41.95136 331.8276 -18.6790038
Jul  3  16.43189 317.3722  -2.2040593
Aug  3 -15.16009 301.3484 -24.8883026
Sep  3 -33.48874 285.3246  -2.8358711
Oct  3 -49.26018 270.8876 -16.1273846
Nov  3 -27.95495 256.4505   7.1044385
Dec  3 -26.66943 245.0737  22.4957092
Jan  4  45.99808 233.6969 -14.7949946
Feb  4  54.85858 225.8087 -26.8673028
Mar  4  31.55457 217.9205 -17.1751046
Apr  4  -8.36346 213.4391 -11.2756080
May  4 -29.89762 208.9576  -2.0599804
Jun  4  41.95136 206.4582 -35.2095181
Jul  4  16.43189 203.9587 -13.1905993
Aug  4 -15.16009 202.3376  -6.5775184
Sep  4 -33.48874 200.7165  21.3722374
Oct  4 -49.26018 199.6404  25.0197607
Nov  4 -27.95495 198.5643  28.3906206
Dec  4 -26.66943 197.6237   8.6457528
Jan  5  45.99808 196.6830 -16.8810894
Feb  5  54.85858 195.4542 -16.3127352
Mar  5  31.55457 194.2253 -25.5798745
Apr  5  -8.36346 192.7008  -0.7373509
May  5 -29.89762 191.1763  16.9213036
Jun  5  41.95136 189.9203 -28.6716366
Jul  5  16.43189 188.6642   3.4038794
Aug  5 -15.16009 187.0519  19.9081981
Sep  5 -33.48874 185.4395  20.8491916
Oct  5 -49.26018 183.3174  13.9427290
Nov  5 -27.95495 181.1953   6.1596030
Dec  5 -26.66943 178.2417   2.9276804
Jan  6  45.99808 175.2881  -8.0862165
Feb  6  54.85858 172.7771 -31.2356297
Mar  6  31.55457 170.2660 -19.0205363
Apr  6  -8.36346 171.1633  13.6001492
May  6 -29.89762 172.0607  11.4369657
Jun  6  41.95136 179.4101 -48.1614458
Jul  6  16.43189 186.7595 -32.1914008
Aug  6 -15.16009 201.0233 -34.6632146
Sep  6 -33.48874 215.2871 -19.8983536
Oct  6 -49.26018 233.9259 -27.4657328
Nov  6 -27.95495 252.5647 -22.9097754
Dec  6 -26.66943 271.4957  -8.4262802
Jan  7  45.99808 290.4267  19.6752406
Feb  7  54.85858 306.8539  36.5874891
Mar  7  31.55457 323.2812  48.8642440
Apr  7  -8.36346 334.4144  58.5490258
May  7 -29.89762 345.5477  50.1499384
Jun  7  41.95136 349.4552 -23.3066049
Jul  7  16.43189 353.3628  -1.8946918
Aug  7 -15.16009 350.3966  11.7634501
Sep  7 -33.48874 347.4305  29.3582668
Oct  7 -49.26018 341.3231   0.8370515
Nov  7 -27.95495 335.2158   4.2391727
Dec  7 -26.66943 327.7158  -0.1463674
Jan  8  45.99808 320.2158   0.6861180
Feb  8  54.85858 312.1037 -10.0622648
Mar  8  31.55457 303.9916  -5.8461411
Apr  8  -8.36346 297.2465  27.3169529
May  8 -29.89762 290.5014   8.3961779
Jun  8  41.95136 285.8915 -38.5428235
Jul  8  16.43189 281.2815 -31.5133686
Aug  8 -15.16009 277.9490  -9.1889228
Sep  8 -33.48874 274.6165  -7.3278023
Oct  8 -49.26018 273.5649   4.0952773
Nov  8 -27.95495 272.5133   9.0416934
Dec  8 -26.66943 273.6413  13.1280782
Jan  9  45.99808 274.7694 -14.1675114
Feb  9  54.85858 275.4009 -21.0594529
Mar  9  31.55457 276.0323   1.9131121
Apr  9  -8.36346 275.7360   3.6274506
May  9 -29.89762 275.4397  34.3579201
Jun  9  41.95136 275.5571   0.3915188
Jul  9  16.43189 275.6745   6.2935739
Aug  9 -15.16009 275.2112 -13.3510846
Sep  9 -33.48874 274.7478 -13.9590683
Oct  9 -49.26018 273.5559 -15.1957458
Nov  9 -27.95495 272.3640  15.4909132
Dec  9 -26.66943 271.7665  20.9028768
Jan 10  45.99808 271.1691   3.4328661
Feb 10  54.85858 271.7463 -18.1049202
Mar 10  31.55457 272.3236 -21.6782001
Apr 10  -8.36346 274.7799  -3.7164553
May 10 -29.89762 277.2362  16.1614205
Jun 10  41.95136 284.2619 -13.1132200
Jul 10  16.43189 291.2875 -23.4194042
Aug 10 -15.16009 305.4444 -37.6843400
Sep 10 -33.48874 319.6013 -35.8126011
Oct 10 -49.26018 338.9845 -43.2243488
Nov 10 -27.95495 358.3677 -17.7127599
Dec 10 -26.66943 378.9493 -19.0798505
Jan 11  45.99808 399.5308   0.8710844
Feb 11  54.85858 417.2404  39.5010457
Mar 11  31.55457 434.9499  48.9955136
Apr 11  -8.36346 445.6574  69.1060843
May 11 -29.89762 456.3648  56.7327860
Jun 11  41.95136 459.0431  21.3055820
Jul 11  16.43189 461.7213  31.6468344
Aug 11 -15.16009 456.9841  18.8759876
Sep 11 -33.48874 452.2469 -12.9581844
Oct 11 -49.26018 442.1414 -17.8812173
Nov 11 -27.95495 432.0359 -25.5809136
Dec 11 -26.66943 420.4204  13.0490101
Jan 12  45.99808 408.8050  12.9969594
Feb 12  54.85858 399.1002  15.8411931
Mar 12  31.55457 389.3955   8.8499332
Apr 12  -8.36346 383.1783 -19.0148485
May 12 -29.89762 376.9611 -14.3634993
Jun 12  41.95136 372.7049 -36.6562368
Jul 12  16.43189 368.4486 -24.3805179
Aug 12 -15.16009 365.8037 -15.9435774
Sep 12 -33.48874 363.1587 -10.1699621
Oct 12 -49.26018 363.2665   9.0936598
Nov 12 -27.95495 363.3743  28.1806183
Dec 12 -26.66943 365.2819  13.4874898
Jan 13  45.99808 367.1895  -1.2876130
Feb 13  54.85858 368.9671 -35.2256368
Mar 13  31.55457 370.7446  14.1008460
Apr 13  -8.36346 373.3665  -4.3029990
May 13 -29.89762 375.9883  -8.0907131
Jun 13  41.95136 382.6997  -7.4510421
Jul 13  16.43189 389.4110 -17.4429148
Aug 13 -15.16009 400.5404 -14.2803262
Sep 13 -33.48874 411.6698 -46.6810629
Oct 13 -49.26018 423.8425 -20.8822852
Nov 13 -27.95495 436.0151 -11.3601710
Dec 13 -26.66943 447.0310  26.6384667
Jan 14  45.99808 458.0468  29.4551300
Feb 14  54.85858 465.5009  45.0405616
Mar 14  31.55457 472.9549  37.7904998
Apr 14  -8.36346 474.6790  22.3844374
May 14 -29.89762 476.4031  20.5945060
Jun 14  41.95136 471.9709  17.3777634
Jul 14  16.43189 467.5386  12.1294771
Aug 14 -15.16009 459.2878  -0.1277547
Sep 14 -33.48874 451.0371 -14.1483117
Oct 14 -49.26018 442.3699  -6.8096889
Nov 14 -27.95495 433.7027 -11.6477296
Dec 14 -26.66943 425.9540   4.8153817
Jan 15  45.99808 418.2054  -2.1034815
Feb 15  54.85858 412.0625 -18.8210363
Mar 15  31.55457 405.9195  -5.1740846
Apr 15  -8.36346 401.7442  -7.0807376
May 15 -29.89762 397.5689  27.5287404
Jun 15  41.95136 395.9512 -16.0025133
Jul 15  16.43189 394.3334 -27.8653107
Aug 15 -15.16009 395.0809   4.2791857
Sep 15 -33.48874 395.8284 -16.8396432
Oct 15 -49.26018 397.7026 -25.0424496
Nov 15 -27.95495 399.5769   0.9780805
Dec 15 -26.66943 401.7079   0.9615521
Jan 16  45.99808 403.8389  12.8630493
Feb 16  54.85858 405.1898  26.9516468
Mar 16  31.55457 406.5407   6.1047507
Apr 16  -8.36346 406.6472   1.0162229
May 16 -29.89762 406.7538  18.0438261
Jun 16  41.95136 405.8559   7.5927502
Jul 16  16.43189 404.9580  -7.3898694
Aug 16 -15.16009 403.2032 -12.5431251
Sep 16 -33.48874 401.4484 -20.9597060
Oct 16 -49.26018 399.5648 -10.9045906
Nov 16 -27.95495 397.6811  16.0738612
Dec 16 -26.66943 395.8279   9.6415730
Jan 17  45.99808 393.9746  11.8273103
Feb 17  54.85858 391.8241  -0.5826454
Mar 17  31.55457 389.6735   1.2719053
Apr 17  -8.36346 386.6159   4.8475995
May 17 -29.89762 383.5582  -0.8605753
Jun 17  41.95136 379.8175  23.5311788
Jul 17  16.43189 376.0767 -25.0086107
Aug 17 -15.16009 372.4280  -2.1679602
Sep 17 -33.48874 368.7794  -9.0906349
Oct 17 -49.26018 365.6305   3.4297195
Nov 17 -27.95495 362.4815  -2.7265894
Dec 17 -26.66943 359.8360   7.7334340
Jan 18  45.99808 357.1904  -9.0885169
Feb 18  54.85858 354.3322   8.0092216
Mar 18  31.55457 351.4740 -13.1285333
Apr 18  -8.36346 347.6922   9.8712167
May 18 -29.89762 343.9105   7.3870977
Jun 18  41.95136 338.8293  24.9193553
Jul 18  16.43189 333.7480  -7.2799307
Aug 18 -15.16009 327.1104   4.5497220
Sep 18 -33.48874 320.4727  -2.7839505
Oct 18 -49.26018 314.1466   6.0135522
Nov 18 -27.95495 307.8206   8.9343914
Dec 18 -26.66943 303.4107   2.0587156
Jan 19  45.99808 299.0009 -20.5989347
Feb 19  54.85858 296.2481 -40.2067174
Mar 19  31.55457 293.4954 -26.0499937
Apr 19  -8.36346 291.8567 -10.4932406
May 19 -29.89762 290.2180  18.9796435
Jun 19  41.95136 289.7485  27.5001566
Jul 19  16.43189 289.2790  -0.7108741
Aug 19 -15.16009 288.8194   8.4406797
Sep 19 -33.48874 288.3598  -4.5710917
Oct 19 -49.26018 286.9206   8.8395799
Nov 19 -27.95495 285.4814   0.3735880
Dec 19 -26.66943 284.8251   8.3443458
Jan 20  45.99808 284.1688 -14.2668709
Feb 20  54.85858 285.8255 -22.2841221
Mar 20  31.55457 287.4823 -23.6368669
Apr 20  -8.36346 290.6451 -15.8816414
May 20 -29.89762 293.8079 -18.1102849
Jun 20  41.95136 296.3825  24.4661053
Jul 20  16.43189 298.9572   9.5109518
Aug 20 -15.16009 299.6349   9.7252247
Sep 20 -33.48874 300.3126  22.6761723
Oct 20 -49.26018 298.8070  45.6532128
Nov 20 -27.95495 297.3014  20.9535898
Dec 20 -26.66943 295.0844   3.5849778
Jan 21  45.99808 292.8675 -31.4656086
Feb 21  54.85858 290.6489 -16.8074892
Mar 21  31.55457 288.4303 -27.0848634
Apr 21  -8.36346 286.6738 -29.2103279
May 21 -29.89762 284.9173 -24.6196615
Jun 21  41.95136 283.7158  35.8328264
Jul 21  16.43189 282.5143  22.7537706
Aug 21 -15.16009 281.0865  11.2736068
Sep 21 -33.48874 279.6586  14.5301177
Oct 21 -49.26018 277.5702  22.6899974
Nov 21 -27.95495 275.4817  10.0732137
Dec 21 -26.66943 273.8256  -5.3561316
Jan 22  45.99808 272.1694 -30.6674513
Feb 22  54.85858 272.7014 -35.2599560
Mar 22  31.55457 273.2334 -30.0879542
Apr 22  -8.36346 276.2482 -13.6847698
May 22 -29.89762 279.2631 -19.3654543
Jun 22  41.95136 283.8047  13.2439533
Jul 22  16.43189 288.3463  13.4218174
Aug 22 -15.16009 294.4807   7.6794391
Sep 22 -33.48874 300.6150  28.6737357
Oct 22 -49.26018 308.0281  25.2320821
Nov 22 -27.95495 315.4412 -16.4862350
Dec 22 -26.66943 324.5872 -35.2177544
Jan 23  45.99808 333.7332 -39.1312482
Feb 23  54.85858 345.1410 -20.5996084
Mar 23  31.55457 356.5489 -14.8034620
Apr 23  -8.36346 370.9280  -7.3645324
May 23 -29.89762 385.3071 -17.0094718
Jun 23  41.95136 401.5560  23.3926244
Jul 23  16.43189 417.8049  16.7631770
Aug 23 -15.16009 432.1446   5.0155203
Sep 23 -33.48874 446.4842  16.2045384
Oct 23 -49.26018 456.5756  18.5845360
Nov 23 -27.95495 466.6671  21.9878702
Dec 23 -26.66943 473.5927  16.6766854
Jan 24  45.99808 480.5184  14.8835263
Feb 24  54.85858 485.5440   3.7973769
Mar 24  31.55457 490.5697  -4.6242660
Apr 24  -8.36346 493.7461 -15.9826427
May 24 -29.89762 496.9225 -27.6248884
Jun 24  41.95136 498.4559   8.5927847
Jul 24  16.43189 499.9892  16.5789141
Aug 24 -15.16009 500.6636  20.5964500
Sep 24 -33.48874 501.3381  16.1506607
Oct 24 -49.26018 500.8663   5.3938403
Nov 24 -27.95495 500.3946   9.0603564
Dec 24 -26.66943 498.8417  -2.6722659
Jan 25  45.99808 497.2888   1.4131374
Feb 25  54.85858 495.5445  -9.2031106
Mar 25  31.55457 493.8003  -3.8548521
Apr 25  -8.36346 491.8384 -13.7749113
May 25 -29.89762 489.8765 -25.5788396
Jun 25  41.95136 486.2256  14.4230744
Jul 25  16.43189 482.5747  18.2934447
Aug 25 -15.16009 477.4900  23.3701294
Sep 25 -33.48874 472.4053  26.8834888
Oct 25 -49.26018 466.5652  29.6949730
Nov 25 -27.95495 460.7252  -6.1702061
Dec 25 -26.66943 454.6667 -16.3972740
Jan 26  45.99808 448.6082 -27.1063162
Feb 26  54.85858 443.3956 -13.7541716
Mar 26  31.55457 438.1829 -18.5375205
Apr 26  -8.36346 435.2883  -9.5248089
May 26 -29.89762 432.3936 -22.5959662
Jun 26  41.95136 432.5187  10.2299124
Jul 26  16.43189 432.6439   5.9242474
Aug 26 -15.16009 434.5425   1.4175628
Sep 26 -33.48874 436.4412  13.5475530
Oct 26 -49.26018 438.7112 -13.1509889
Nov 26 -27.95495 440.9811  -7.4261944
Dec 26 -26.66943 444.6150 -12.1455334
Jan 27  45.99808 448.2488   6.5531531
Feb 27  54.85858 454.8135   4.3279668
Mar 27  31.55457 461.3781 -17.4327130
Apr 27  -8.36346 472.2917 -33.8282219
May 27 -29.89762 483.2052 -38.9075998
Jun 27  41.95136 501.3033  -5.2546267
Jul 27  16.43189 519.4013  -9.8331973
Aug 27 -15.16009 545.6425 -41.9824071
Sep 27 -33.48874 571.8837 -18.1949421
Oct 27 -49.26018 602.1557 -48.4955371
Nov 27 -27.95495 632.4277 -35.9727956
Dec 27 -26.66943 661.2472 -23.9777699
Jan 28  45.99808 690.0666  81.9352813
Feb 28  54.85858 714.1508  61.8905786
Mar 28  31.55457 738.2350  66.1103823
Apr 28  -8.36346 754.3100  36.0535045
May 28 -29.89762 770.3849  21.8127577
Jun 28  41.95136 776.2424  38.7062112
Jul 28  16.43189 782.1000  22.3681211
Aug 28 -15.16009 779.2805   5.4796025
Sep 28 -33.48874 776.4610   9.2277588
Oct 28 -49.26018 768.9286   4.7315754
Nov 28 -27.95495 761.3962 -10.3412714
Dec 28 -26.66943 753.4288  -7.2594006
Jan 29  45.99808 745.4614  25.9404957
Feb 29  54.85858 740.1094   8.3320528
Mar 29  31.55457 734.7573 -13.8118835
Apr 29  -8.36346 731.9049 -34.5414344
May 29 -29.89762 729.0525 -68.7548544
Jun 29  41.95136 727.9191  -4.3704461
Jul 29  16.43189 726.7857  14.4824186
Aug 29 -15.16009 727.1458  20.2143188
Sep 29 -33.48874 727.5058   8.5828937
Oct 29 -49.26018 726.8900   5.6701344
Nov 29 -27.95495 726.2742  11.1807117
Dec 29 -26.66943 722.8541   6.0152799
Jan 30  45.99808 719.4341  19.3678736
Feb 30  54.85858 714.0650  41.9764520
Mar 30  31.55457 708.6959  15.3495369
Apr 30  -8.36346 702.4796 -37.3161406
May 30 -29.89762 696.2633 -51.2656873
Jun 30  41.95136 688.4369  14.9117515
Jul 30  16.43189 680.6105  -2.9423534
Aug 30 -15.16009 672.3135  18.5466386
Sep 30 -33.48874 664.0164  13.1723053
Oct 30 -49.26018 654.8991  16.4610536
Nov 30 -27.95495 645.7818  16.7731385
Dec 30 -26.66943 636.6996 -22.0301809
Jan 31  45.99808 627.6174  16.0845252
Feb 31  54.85858 618.3012   0.7402100
Mar 31  31.55457 608.9850   7.3604013
Apr 31  -8.36346 599.3636 -22.2001353
May 31 -29.89762 589.7422 -14.1445410
Jun 31  41.95136 579.9137  10.7349713
> m$win
   s    t    l 
3661   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
367   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/wessaorg/rcomp/tmp/1orgs1352746313.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/2mj2t1352746313.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$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3b33b1352746313.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$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$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4w00w1352746313.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$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/5q6c71352746313.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/6ki4n1352746313.tab") 
> 
> try(system("convert tmp/1orgs1352746313.ps tmp/1orgs1352746313.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mj2t1352746313.ps tmp/2mj2t1352746313.png",intern=TRUE))
character(0)
> try(system("convert tmp/3b33b1352746313.ps tmp/3b33b1352746313.png",intern=TRUE))
character(0)
> try(system("convert tmp/4w00w1352746313.ps tmp/4w00w1352746313.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  6.788   0.429   7.364