R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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(1.3866
+ ,1.3582
+ ,1.3332
+ ,1.3595
+ ,1.3617
+ ,1.3684
+ ,1.3394
+ ,1.3262
+ ,1.3173
+ ,1.3085
+ ,1.327
+ ,1.3182
+ ,1.293
+ ,1.291
+ ,1.2984
+ ,1.2795
+ ,1.299
+ ,1.3174
+ ,1.326
+ ,1.3111
+ ,1.2816
+ ,1.276
+ ,1.2849
+ ,1.2818
+ ,1.2829
+ ,1.2796
+ ,1.3008
+ ,1.2967
+ ,1.2938
+ ,1.2833
+ ,1.2823
+ ,1.2765
+ ,1.2634
+ ,1.2596
+ ,1.2705
+ ,1.2591
+ ,1.2798
+ ,1.2763
+ ,1.2795
+ ,1.2782
+ ,1.2644
+ ,1.2596
+ ,1.2615
+ ,1.2555
+ ,1.2555
+ ,1.2658
+ ,1.2565
+ ,1.2783
+ ,1.2786
+ ,1.2782
+ ,1.2905
+ ,1.3042
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+ ,1.313
+ ,1.3671
+ ,1.3549
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+ ,1.3494
+ ,1.3607
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+ ,1.3273
+ ,1.3276
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+ ,1.2947
+ ,1.305
+ ,1.3232
+ ,1.3125
+ ,1.2992
+ ,1.3266
+ ,1.3275
+ ,1.3223
+ ,1.3403
+ ,1.3322
+ ,1.3363
+ ,1.3425
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+ ,1.3866
+ ,1.3959
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+ ,1.4004
+ ,1.385
+ ,1.389
+ ,1.384
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+ ,1.399
+ ,1.3901
+ ,1.3975
+ ,1.3991
+ ,1.4089
+ ,1.413
+ ,1.409
+ ,1.4217
+ ,1.4223
+ ,1.4191
+ ,1.4229
+ ,1.4227
+ ,1.4269
+ ,1.4229
+ ,1.4104
+ ,1.4053
+ ,1.4138
+ ,1.4303
+ ,1.4384
+ ,1.441
+ ,1.437
+ ,1.4357
+ ,1.4202
+ ,1.4166
+ ,1.417
+ ,1.4293
+ ,1.4294
+ ,1.4072
+ ,1.4101
+ ,1.4112
+ ,1.4243
+ ,1.433
+ ,1.4323
+ ,1.4324
+ ,1.427
+ ,1.4268
+ ,1.4364
+ ,1.4272
+ ,1.4314
+ ,1.422
+ ,1.4335
+ ,1.4262
+ ,1.433
+ ,1.4473
+ ,1.4522
+ ,1.4545
+ ,1.4594
+ ,1.4561
+ ,1.4611
+ ,1.4671
+ ,1.4712
+ ,1.4705
+ ,1.4658
+ ,1.478
+ ,1.4783
+ ,1.4768
+ ,1.467
+ ,1.465
+ ,1.4549
+ ,1.4643
+ ,1.4539
+ ,1.4537
+ ,1.4616
+ ,1.4722
+ ,1.4694
+ ,1.4763
+ ,1.475
+ ,1.4765
+ ,1.4864
+ ,1.4881
+ ,1.4864
+ ,1.4869
+ ,1.4918
+ ,1.4971
+ ,1.4921
+ ,1.5
+ ,1.502
+ ,1.5019
+ ,1.4874
+ ,1.4785
+ ,1.4788
+ ,1.48
+ ,1.4772
+ ,1.4658
+ ,1.4761
+ ,1.4867
+ ,1.4862
+ ,1.4984
+ ,1.4966
+ ,1.5037
+ ,1.4922
+ ,1.4868
+ ,1.4965
+ ,1.4875
+ ,1.4957
+ ,1.4863
+ ,1.4815
+ ,1.4968
+ ,1.4969
+ ,1.5083
+ ,1.5071
+ ,1.4918
+ ,1.5023
+ ,1.5074
+ ,1.509
+ ,1.512
+ ,1.5068
+ ,1.4787
+ ,1.4774
+ ,1.4768
+ ,1.473
+ ,1.4757
+ ,1.4647
+ ,1.4541
+ ,1.456
+ ,1.4343
+ ,1.4337
+ ,1.4368
+ ,1.4279
+ ,1.4276
+ ,1.4398
+ ,1.4405
+ ,1.4433
+ ,1.4338
+ ,1.4406
+ ,1.4389
+ ,1.4442
+ ,1.435
+ ,1.4304
+ ,1.4273
+ ,1.4528
+ ,1.4481
+ ,1.4563
+ ,1.4486
+ ,1.4374
+ ,1.4369
+ ,1.4279
+ ,1.4132
+ ,1.4064
+ ,1.4135
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+ ,1.4085
+ ,1.4072
+ ,1.3999
+ ,1.3966
+ ,1.3913
+ ,1.3937
+ ,1.3984
+ ,1.3847
+ ,1.3691
+ ,1.3675
+ ,1.376
+ ,1.374
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+ ,1.3356
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+ ,1.3482
+ ,1.3479
+ ,1.3468
+ ,1.3396
+ ,1.334
+ ,1.3296
+ ,1.3384
+ ,1.3585
+ ,1.3583
+ ,1.3615
+ ,1.3544
+ ,1.3535
+ ,1.3432
+ ,1.3486
+ ,1.3373
+ ,1.3339
+ ,1.3311
+ ,1.3321
+ ,1.329
+ ,1.3245
+ ,1.3256
+ ,1.3315
+ ,1.3238
+ ,1.3089
+ ,1.2924
+ ,1.2727
+ ,1.2746
+ ,1.2969
+ ,1.2698
+ ,1.2686
+ ,1.2587
+ ,1.2492
+ ,1.2349
+ ,1.2428
+ ,1.227
+ ,1.2334
+ ,1.2497
+ ,1.236
+ ,1.2223
+ ,1.2309
+ ,1.2255
+ ,1.2384
+ ,1.2307
+ ,1.2155
+ ,1.2218
+ ,1.2268
+ ,1.206
+ ,1.1959
+ ,1.1942
+ ,1.201
+ ,1.2045
+ ,1.2127
+ ,1.2249
+ ,1.2258
+ ,1.2277
+ ,1.2363
+ ,1.2372
+ ,1.2391
+ ,1.2258
+ ,1.2271
+ ,1.2262
+ ,1.2294
+ ,1.2339
+ ,1.2198
+ ,1.2271
+ ,1.2328
+ ,1.2548
+ ,1.2531
+ ,1.2579
+ ,1.2567
+ ,1.266
+ ,1.2637
+ ,1.2572
+ ,1.2569
+ ,1.2703
+ ,1.2828
+ ,1.3
+ ,1.2957
+ ,1.2844
+ ,1.2817
+ ,1.285
+ ,1.2897
+ ,1.2931
+ ,1.3033
+ ,1.2992
+ ,1.3069
+ ,1.3028
+ ,1.3073
+ ,1.3221
+ ,1.3206
+ ,1.3184
+ ,1.3176
+ ,1.3253
+ ,1.3133
+ ,1.3016
+ ,1.279
+ ,1.2799
+ ,1.282
+ ,1.286
+ ,1.288
+ ,1.2836
+ ,1.2711
+ ,1.2704
+ ,1.2611
+ ,1.2613
+ ,1.2693
+ ,1.2713
+ ,1.27
+ ,1.268
+ ,1.28
+ ,1.2818
+ ,1.2834
+ ,1.2874
+ ,1.2744
+ ,1.2697
+ ,1.2715
+ ,1.2725
+ ,1.2801
+ ,1.285
+ ,1.2989
+ ,1.3078
+ ,1.306
+ ,1.3074
+ ,1.312
+ ,1.3364
+ ,1.3323
+ ,1.3412
+ ,1.3477
+ ,1.346
+ ,1.3611
+ ,1.3648
+ ,1.3726
+ ,1.3705
+ ,1.378
+ ,1.3856
+ ,1.397
+ ,1.3874
+ ,1.3936
+ ,1.3833
+ ,1.3958
+ ,1.4101
+ ,1.4089
+ ,1.3896
+ ,1.3859
+ ,1.3861
+ ,1.4016
+ ,1.3934
+ ,1.4031
+ ,1.3912
+ ,1.3803
+ ,1.3857
+ ,1.3857
+ ,1.3926
+ ,1.4018
+ ,1.4014
+ ,1.4244
+ ,1.4084
+ ,1.3917
+ ,1.3945
+ ,1.377
+ ,1.37
+ ,1.3711
+ ,1.3626
+ ,1.3612
+ ,1.3481
+ ,1.3647
+ ,1.3674
+ ,1.3647
+ ,1.3496
+ ,1.3339
+ ,1.3321
+ ,1.3225
+ ,1.3146
+ ,1.2998)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '5'
> main = 'Seasonal Decomposition by Loess'
> par1 <- 5
> 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
Time Series:
Start = c(1, 1) 
End = c(99, 1) 
Frequency = 5 
          seasonal    trend     remainder
 1.0 -0.0011337034 1.368933  1.880096e-02
 1.2 -0.0006619511 1.364769 -5.906719e-03
 1.4  0.0002066172 1.360908 -2.791431e-02
 1.6  0.0004998966 1.356627  2.373178e-03
 1.8  0.0010891406 1.353636  6.974528e-03
 2.0 -0.0011337034 1.350091  1.944284e-02
 2.2 -0.0006619511 1.342269 -2.206565e-03
 2.4  0.0002066172 1.332138 -6.144289e-03
 2.6  0.0004998966 1.324046 -7.245838e-03
 2.8  0.0010891406 1.318703 -1.129202e-02
 3.0 -0.0011337034 1.313554  1.457999e-02
 3.2 -0.0006619511 1.308664  1.019764e-02
 3.4  0.0002066172 1.303552 -1.075845e-02
 3.6  0.0004998966 1.296999 -6.499030e-03
 3.8  0.0010891406 1.293891  3.420217e-03
 4.0 -0.0011337034 1.297073 -1.643902e-02
 4.2 -0.0006619511 1.302799 -3.136839e-03
 4.4  0.0002066172 1.306705  1.048838e-02
 4.6  0.0004998966 1.306777  1.872327e-02
 4.8  0.0010891406 1.302314  7.696380e-03
 5.0 -0.0011337034 1.294942 -1.220787e-02
 5.2 -0.0006619511 1.287308 -1.064575e-02
 5.4  0.0002066172 1.282532  2.161093e-03
 5.6  0.0004998966 1.282252 -9.516702e-04
 5.8  0.0010891406 1.285139 -3.328281e-03
 6.0 -0.0011337034 1.288271 -7.537677e-03
 6.2 -0.0006619511 1.290508  1.095362e-02
 6.4  0.0002066172 1.291359  5.134452e-03
 6.6  0.0004998966 1.290231  3.068614e-03
 6.8  0.0010891406 1.286090 -3.878907e-03
 7.0 -0.0011337034 1.279921  3.512490e-03
 7.2 -0.0006619511 1.274046  3.115815e-03
 7.4  0.0002066172 1.269721 -6.527192e-03
 7.6  0.0004998966 1.266745 -7.645300e-03
 7.8  0.0010891406 1.266700  2.710729e-03
 8.0 -0.0011337034 1.269321 -9.087566e-03
 8.2 -0.0006619511 1.272560  7.902377e-03
 8.4  0.0002066172 1.274726  1.367109e-03
 8.6  0.0004998966 1.274714  4.286489e-03
 8.8  0.0010891406 1.272014  5.096838e-03
 9.0 -0.0011337034 1.268166 -2.632759e-03
 9.2 -0.0006619511 1.263772 -3.509892e-03
 9.4  0.0002066172 1.260298  9.949418e-04
 9.6  0.0004998966 1.259189 -4.189363e-03
 9.8  0.0010891406 1.259734 -5.323138e-03
10.0 -0.0011337034 1.262463  4.470536e-03
10.2 -0.0006619511 1.266853 -9.690795e-03
10.4  0.0002066172 1.271608  6.485358e-03
10.6  0.0004998966 1.277475  6.251668e-04
10.8  0.0010891406 1.284330 -7.219036e-03
11.0 -0.0011337034 1.290057  1.576376e-03
11.2 -0.0006619511 1.298428  6.433847e-03
11.4  0.0002066172 1.311993 -1.799970e-02
11.6  0.0004998966 1.325858 -1.335746e-02
11.8  0.0010891406 1.337954  2.805678e-02
12.0 -0.0011337034 1.348197  7.836996e-03
12.2 -0.0006619511 1.353731  2.731239e-03
12.4  0.0002066172 1.353332 -2.838571e-03
12.6  0.0004998966 1.348976 -7.592539e-05
12.8  0.0010891406 1.343050  1.656052e-02
13.0 -0.0011337034 1.337592 -6.958490e-03
13.2 -0.0006619511 1.332641 -1.267856e-02
13.4  0.0002066172 1.329915  6.786084e-04
13.6  0.0004998966 1.331910 -7.809492e-03
13.8  0.0010891406 1.335742  2.368487e-03
14.0 -0.0011337034 1.336965  6.668564e-03
14.2 -0.0006619511 1.335909  1.435319e-02
14.4  0.0002066172 1.333340 -8.047043e-03
14.6  0.0004998966 1.329467 -6.866951e-03
14.8  0.0010891406 1.325380  8.304900e-04
15.0 -0.0011337034 1.322640  6.094118e-03
15.2 -0.0006619511 1.319093 -1.131161e-03
15.4  0.0002066172 1.313335  6.058542e-03
15.6  0.0004998966 1.306994 -1.693765e-03
15.8  0.0010891406 1.302038 -6.526991e-03
16.0 -0.0011337034 1.300113 -5.779177e-03
16.2 -0.0006619511 1.302149 -6.786997e-03
16.4  0.0002066172 1.305409 -6.160692e-04
16.6  0.0004998966 1.308512  1.418784e-02
16.8  0.0010891406 1.312782 -1.371589e-03
17.0 -0.0011337034 1.316369 -1.603490e-02
17.2 -0.0006619511 1.318952  8.309503e-03
17.4  0.0002066172 1.323571  3.722188e-03
17.6  0.0004998966 1.328709 -6.908611e-03
17.8  0.0010891406 1.332000  7.211227e-03
18.0 -0.0011337034 1.335649 -2.315260e-03
18.2 -0.0006619511 1.341149 -4.187178e-03
18.4  0.0002066172 1.347263 -4.969135e-03
18.6  0.0004998966 1.353098  3.802200e-03
18.8  0.0010891406 1.357315  9.896220e-03
19.0 -0.0011337034 1.358735  4.698416e-03
19.2 -0.0006619511 1.357634 -6.719749e-04
19.4  0.0002066172 1.356511 -4.918025e-03
19.6  0.0004998966 1.357807 -8.906599e-03
19.8  0.0010891406 1.362593 -2.482502e-03
20.0 -0.0011337034 1.370947 -8.135595e-04
20.2 -0.0006619511 1.380181 -2.418568e-03
20.4  0.0002066172 1.387043  9.950631e-03
20.6  0.0004998966 1.391071  9.429333e-03
20.8  0.0010891406 1.393130 -3.419318e-03
21.0 -0.0011337034 1.395393 -4.159166e-03
21.2 -0.0006619511 1.399794 -1.353224e-02
21.4  0.0002066172 1.406165  3.428145e-03
21.6  0.0004998966 1.412518  8.982467e-03
21.8  0.0010891406 1.416833  5.877653e-03
22.0 -0.0011337034 1.416936  4.898019e-03
22.2 -0.0006619511 1.412242 -2.079861e-03
22.4  0.0002066172 1.406831  1.066197e-02
22.6  0.0004998966 1.403449 -1.734933e-02
22.8  0.0010891406 1.400960 -6.149412e-03
23.0 -0.0011337034 1.398977  1.235628e-02
23.2 -0.0006619511 1.397772 -2.100202e-04
23.4  0.0002066172 1.395404  4.789431e-03
23.6  0.0004998966 1.391872 -7.371460e-03
23.8  0.0010891406 1.389714 -1.803137e-03
24.0 -0.0011337034 1.388934 -3.800779e-03
24.2 -0.0006619511 1.389258  3.404003e-03
24.4  0.0002066172 1.390991  2.002189e-03
24.6  0.0004998966 1.393388 -8.088292e-03
24.8  0.0010891406 1.395396  1.315075e-03
25.0 -0.0011337034 1.398256  5.777352e-03
25.2 -0.0006619511 1.401803 -7.141023e-03
25.4  0.0002066172 1.404693  4.700840e-03
25.6  0.0004998966 1.406791 -1.491341e-03
25.8  0.0010891406 1.407925  4.385487e-03
26.0 -0.0011337034 1.406803  3.930700e-03
26.2 -0.0006619511 1.404026  1.536330e-03
26.4  0.0002066172 1.400888 -1.948364e-04
26.6  0.0004998966 1.397949 -8.749182e-03
26.8  0.0010891406 1.396009  4.801476e-03
27.0 -0.0011337034 1.395087 -3.853326e-03
27.2 -0.0006619511 1.395193  4.469394e-03
27.4  0.0002066172 1.396029 -6.135886e-03
27.6  0.0004998966 1.398469 -1.468569e-03
27.8  0.0010891406 1.401885 -3.874264e-03
28.0 -0.0011337034 1.405868  4.165648e-03
28.2 -0.0006619511 1.410360  3.301813e-03
28.4  0.0002066172 1.414351 -5.557800e-03
28.6  0.0004998966 1.417052  4.148160e-03
28.8  0.0010891406 1.419291  1.919905e-03
29.0 -0.0011337034 1.421366 -1.132689e-03
29.2 -0.0006619511 1.422556  1.006118e-03
29.4  0.0002066172 1.422582 -8.829184e-05
29.6  0.0004998966 1.420982  5.417618e-03
29.8  0.0010891406 1.418178  3.632972e-03
30.0 -0.0011337034 1.416168 -4.634146e-03
30.2 -0.0006619511 1.416576 -1.061452e-02
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94.6  0.0004998966 1.389511 -4.310898e-03
94.8  0.0010891406 1.394141 -2.630586e-03
95.0 -0.0011337034 1.400393  2.541069e-03
95.2 -0.0006619511 1.404935 -2.873019e-03
95.4  0.0002066172 1.405802  1.839126e-02
95.6  0.0004998966 1.403610  4.290260e-03
95.8  0.0010891406 1.397796 -7.185052e-03
96.0 -0.0011337034 1.389085  6.548465e-03
96.2 -0.0006619511 1.381180 -3.518085e-03
96.4  0.0002066172 1.374674 -4.880958e-03
96.6  0.0004998966 1.368522  2.077863e-03
96.8  0.0010891406 1.363703 -2.192417e-03
97.0 -0.0011337034 1.361379  9.542330e-04
97.2 -0.0006619511 1.360789 -1.202670e-02
97.4  0.0002066172 1.360613  3.880640e-03
97.6  0.0004998966 1.359230  7.670563e-03
97.8  0.0010891406 1.355624  7.987170e-03
98.0 -0.0011337034 1.349045  1.689084e-03
98.2 -0.0006619511 1.340196 -5.633587e-03
98.4  0.0002066172 1.330720  1.173241e-03
98.6  0.0004998966 1.321169  8.313340e-04
98.8  0.0010891406 1.311724  1.786513e-03
99.0 -0.0011337034 1.302343 -1.409096e-03
> m$win
   s    t    l 
4911    9    5 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
492   1   1 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/148d61292335871.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2ficr1292335871.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
> acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3ficr1292335871.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4qrtc1292335871.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Component',header=TRUE)
> a<-table.element(a,'Window',header=TRUE)
> a<-table.element(a,'Degree',header=TRUE)
> a<-table.element(a,'Jump',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,m$win['s'])
> a<-table.element(a,m$deg['s'])
> a<-table.element(a,m$jump['s'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,m$win['t'])
> a<-table.element(a,m$deg['t'])
> a<-table.element(a,m$jump['t'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Low-pass',header=TRUE)
> a<-table.element(a,m$win['l'])
> a<-table.element(a,m$deg['l'])
> a<-table.element(a,m$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/5eaq51292335871.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$time.series[i,'remainder'])
+ a<-table.element(a,m$time.series[i,'seasonal'])
+ a<-table.element(a,m$time.series[i,'trend'])
+ a<-table.element(a,m$time.series[i,'remainder'])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6717q1292335871.tab") 
> 
> try(system("convert tmp/148d61292335871.ps tmp/148d61292335871.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ficr1292335871.ps tmp/2ficr1292335871.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ficr1292335871.ps tmp/3ficr1292335871.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qrtc1292335871.ps tmp/4qrtc1292335871.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  7.510   1.031  15.727