USAccDeaths

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
library(ahead)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=MASS::glm.nb, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8268.702 6521.054 10016.351
## Feb 1979       7309.036 5561.388  9056.685
## Mar 1979       8154.790 6407.141  9902.438
## Apr 1979       8531.009 6783.361 10278.658
## May 1979       9393.212 7645.563 11140.860
## Jun 1979       9741.987 7994.338 11489.636
## Jul 1979      11003.191 9255.542 12750.839
## Aug 1979       9835.330 8087.681 11582.978
## Sep 1979       8712.490 6964.841 10460.138
## Oct 1979       9231.324 7483.675 10978.972
## Nov 1979       8576.554 6828.905 10324.203
## Dec 1979       9248.999 7501.351 10996.648
## Jan 1980       8268.712 6521.064 10016.361
## Feb 1980       7309.045 5561.397  9056.694
## Mar 1980       8154.799 6407.151  9902.448
## Apr 1980       8531.020 6783.371 10278.668
## May 1980       9393.223 7645.574 11140.872
## Jun 1980       9741.999 7994.350 11489.647
## Jul 1980      11003.204 9255.555 12750.852
## Aug 1980       9835.341 8087.693 11582.990
## Sep 1980       8712.500 6964.852 10460.149
## Oct 1980       9231.335 7483.686 10978.983
## Nov 1980       8576.564 6828.916 10324.213
## Dec 1980       9249.010 7501.362 10996.659
## Jan 1981       8268.722 6521.074 10016.371
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=stats::glm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8284.993 6498.136 10071.849
## Feb 1979       7329.723 5542.867  9116.579
## Mar 1979       8184.884 6398.028  9971.741
## Apr 1979       8569.831 6782.974 10356.687
## May 1979       9444.036 7657.180 11230.893
## Jun 1979       9803.078 8016.222 11589.935
## Jul 1979      11081.655 9294.799 12868.512
## Aug 1979       9913.926 8127.070 11700.783
## Sep 1979       8789.608 7002.751 10576.464
## Oct 1979       9320.974 7534.118 11107.831
## Nov 1979       8667.223 6880.367 10454.079
## Dec 1979       9354.733 7567.876 11141.589
## Jan 1980       8370.352 6583.495 10157.208
## Feb 1980       7405.175 5618.319  9192.032
## Mar 1980       8269.068 6482.211 10055.924
## Apr 1980       8657.898 6871.041 10444.754
## May 1980       9541.004 7754.147 11327.860
## Jun 1980       9903.646 8116.790 11690.503
## Jul 1980      11195.243 9408.387 12982.099
## Aug 1980      10015.458 8228.602 11802.314
## Sep 1980       8879.548 7092.692 10666.404
## Oct 1980       9416.271 7629.414 11203.127
## Nov 1980       8755.760 6968.904 10542.617
## Dec 1980       9450.212 7663.355 11237.068
## Jan 1981       8455.711 6668.855 10242.567
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=MASS::rlm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8286.973 6502.984 10070.961
## Feb 1979       7332.237 5548.249  9116.225
## Mar 1979       8188.542 6404.554  9972.530
## Apr 1979       8574.549 6790.561 10358.537
## May 1979       9450.213 7666.225 11234.201
## Jun 1979       9810.503 8026.515 11594.491
## Jul 1979      11091.191 9307.203 12875.179
## Aug 1979       9923.478 8139.490 11707.467
## Sep 1979       8798.980 7014.992 10582.968
## Oct 1979       9331.870 7547.882 11115.858
## Nov 1979       8678.242 6894.254 10462.231
## Dec 1979       9367.583 7583.595 11151.571
## Jan 1980       8382.704 6598.716 10166.693
## Feb 1980       7416.858 5632.870  9200.847
## Mar 1980       8282.955 6498.967 10066.943
## Apr 1980       8673.317 6889.329 10457.306
## May 1980       9558.964 7774.976 11342.952
## Jun 1980       9923.292 8139.304 11707.280
## Jul 1980      11218.582 9434.594 13002.570
## Aug 1980      10037.348 8253.360 11821.336
## Sep 1980       8899.850 7115.862 10683.838
## Oct 1980       9438.747 7654.758 11222.735
## Nov 1980       8777.538 6993.550 10561.526
## Dec 1980       9474.664 7690.676 11258.652
## Jan 1981       8478.436 6694.448 10262.424
plot(obj)

#(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=rvfl::rvfl, attention=FALSE)))
#plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=MASS::lqs, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8281.125 6499.563 10062.686
## Feb 1979       7324.811 5543.249  9106.373
## Mar 1979       8177.738 6396.176  9959.300
## Apr 1979       8560.612 6779.050 10342.174
## May 1979       9431.968 7650.406 11213.530
## Jun 1979       9788.572 8007.010 11570.134
## Jul 1979      11063.024 9281.462 12844.585
## Aug 1979       9895.263 8113.701 11676.825
## Sep 1979       8771.296 6989.734 10552.858
## Oct 1979       9299.687 7518.125 11081.248
## Nov 1979       8645.693 6864.132 10427.255
## Dec 1979       9329.626 7548.064 11111.188
## Jan 1980       8346.217 6564.655 10127.779
## Feb 1980       7382.349 5600.787  9163.911
## Mar 1980       8241.934 6460.372 10023.496
## Apr 1980       8627.770 6846.208 10409.332
## May 1980       9505.913 7724.351 11287.475
## Jun 1980       9865.262 8083.701 11646.824
## Jul 1980      11149.642 9368.081 12931.204
## Aug 1980       9972.689 8191.127 11754.250
## Sep 1980       8839.882 7058.320 10621.444
## Oct 1980       9372.357 7590.795 11153.919
## Nov 1980       8713.209 6931.648 10494.771
## Dec 1980       9402.436 7620.874 11183.997
## Jan 1981       8411.310 6629.748 10192.872
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=stats::lm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8284.993 6498.136 10071.849
## Feb 1979       7329.723 5542.867  9116.579
## Mar 1979       8184.884 6398.028  9971.741
## Apr 1979       8569.831 6782.974 10356.687
## May 1979       9444.036 7657.180 11230.893
## Jun 1979       9803.078 8016.222 11589.935
## Jul 1979      11081.655 9294.799 12868.512
## Aug 1979       9913.926 8127.070 11700.783
## Sep 1979       8789.608 7002.751 10576.464
## Oct 1979       9320.974 7534.118 11107.831
## Nov 1979       8667.223 6880.367 10454.079
## Dec 1979       9354.733 7567.876 11141.589
## Jan 1980       8370.352 6583.495 10157.208
## Feb 1980       7405.175 5618.319  9192.032
## Mar 1980       8269.068 6482.211 10055.924
## Apr 1980       8657.898 6871.041 10444.754
## May 1980       9541.004 7754.147 11327.860
## Jun 1980       9903.646 8116.790 11690.503
## Jul 1980      11195.243 9408.387 12982.099
## Aug 1980      10015.458 8228.602 11802.314
## Sep 1980       8879.548 7092.692 10666.404
## Oct 1980       9416.271 7629.414 11203.127
## Nov 1980       8755.760 6968.904 10542.617
## Dec 1980       9450.212 7663.355 11237.068
## Jan 1981       8455.711 6668.855 10242.567
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=gam::gam, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8284.993 6498.136 10071.849
## Feb 1979       7329.723 5542.867  9116.579
## Mar 1979       8184.884 6398.028  9971.741
## Apr 1979       8569.831 6782.974 10356.687
## May 1979       9444.036 7657.180 11230.893
## Jun 1979       9803.078 8016.222 11589.935
## Jul 1979      11081.655 9294.799 12868.512
## Aug 1979       9913.926 8127.070 11700.783
## Sep 1979       8789.608 7002.751 10576.464
## Oct 1979       9320.974 7534.118 11107.831
## Nov 1979       8667.223 6880.367 10454.079
## Dec 1979       9354.733 7567.876 11141.589
## Jan 1980       8370.352 6583.495 10157.208
## Feb 1980       7405.175 5618.319  9192.032
## Mar 1980       8269.068 6482.211 10055.924
## Apr 1980       8657.898 6871.041 10444.754
## May 1980       9541.004 7754.147 11327.860
## Jun 1980       9903.646 8116.790 11690.503
## Jul 1980      11195.243 9408.387 12982.099
## Aug 1980      10015.458 8228.602 11802.314
## Sep 1980       8879.548 7092.692 10666.404
## Oct 1980       9416.271 7629.414 11203.127
## Nov 1980       8755.760 6968.904 10542.617
## Dec 1980       9450.212 7663.355 11237.068
## Jan 1981       8455.711 6668.855 10242.567
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=quantreg::rq, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8285.436 6512.270 10058.601
## Feb 1979       7330.285 5557.120  9103.451
## Mar 1979       8185.703 6412.537  9958.868
## Apr 1979       8570.886 6797.721 10344.051
## May 1979       9445.418 7672.253 11218.583
## Jun 1979       9804.739 8031.574 11577.904
## Jul 1979      11083.788 9310.623 12856.954
## Aug 1979       9916.063 8142.898 11689.228
## Sep 1979       8791.704 7018.539 10564.869
## Oct 1979       9323.412 7550.246 11096.577
## Nov 1979       8669.688 6896.523 10442.853
## Dec 1979       9357.607 7584.442 11130.773
## Jan 1980       8373.115 6599.950 10146.280
## Feb 1980       7407.789 5634.623  9180.954
## Mar 1980       8272.174 6499.009 10045.339
## Apr 1980       8661.347 6888.182 10434.512
## May 1980       9545.021 7771.856 11318.187
## Jun 1980       9908.041 8134.876 11681.206
## Jul 1980      11200.464 9427.298 12973.629
## Aug 1980      10020.355 8247.189 11793.520
## Sep 1980       8884.089 7110.924 10657.255
## Oct 1980       9421.298 7648.133 11194.464
## Nov 1980       8760.632 6987.466 10533.797
## Dec 1980       9455.681 7682.516 11228.847
## Jan 1981       8460.794 6687.629 10233.960
plot(obj)

AirPassengers

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=MASS::glm.nb, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       441.8584 312.3678 571.3490
## Feb 1961       415.3209 285.8303 544.8115
## Mar 1961       470.6764 341.1858 600.1669
## Apr 1961       466.2311 336.7405 595.7217
## May 1961       477.8911 348.4006 607.3817
## Jun 1961       552.4859 422.9953 681.9765
## Jul 1961       618.1428 488.6522 747.6334
## Aug 1961       611.8016 482.3110 741.2922
## Sep 1961       517.7926 388.3021 647.2832
## Oct 1961       448.5274 319.0368 578.0179
## Nov 1961       389.6467 260.1561 519.1373
## Dec 1961       432.9262 303.4356 562.4168
## Jan 1962       441.9022 312.4116 571.3927
## Feb 1962       415.3620 285.8714 544.8526
## Mar 1962       470.7230 341.2324 600.2136
## Apr 1962       466.2773 336.7867 595.7678
## May 1962       477.9385 348.4479 607.4291
## Jun 1962       552.5406 423.0500 682.0312
## Jul 1962       618.2040 488.7134 747.6946
## Aug 1962       611.8622 482.3716 741.3528
## Sep 1962       517.8439 388.3533 647.3345
## Oct 1962       448.5718 319.0812 578.0624
## Nov 1962       389.6853 260.1947 519.1759
## Dec 1962       432.9691 303.4785 562.4596
## Jan 1963       441.9459 312.4553 571.4365
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=stats::glm, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.7666 345.3856 542.1477
## Feb 1961       418.3980 320.0170 516.7791
## Mar 1961       475.6182 377.2371 573.9992
## Apr 1961       472.5670 374.1859 570.9481
## May 1961       485.8623 387.4812 584.2433
## Jun 1961       563.4085 465.0275 661.7896
## Jul 1961       632.2736 533.8925 730.6546
## Aug 1961       627.6780 529.2969 726.0590
## Sep 1961       532.8294 434.4483 631.2105
## Oct 1961       462.9386 364.5575 561.3196
## Nov 1961       403.3700 304.9890 501.7511
## Dec 1961       449.5115 351.1304 547.8926
## Jan 1962       460.1967 361.8157 558.5778
## Feb 1962       433.8412 335.4601 532.2223
## Mar 1962       493.1195 394.7385 591.5006
## Apr 1962       489.9029 391.5219 588.2840
## May 1962       503.6316 405.2506 602.0127
## Jun 1962       583.9514 485.5703 682.3324
## Jul 1962       655.2575 556.8764 753.6386
## Aug 1962       650.4259 552.0448 748.8070
## Sep 1962       552.0818 453.7007 650.4628
## Oct 1962       479.6154 381.2344 577.9965
## Nov 1962       417.8575 319.4764 516.2386
## Dec 1962       465.6080 367.2269 563.9891
## Jan 1963       476.6268 378.2458 575.0079
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=MASS::rlm, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.7757 345.5306 542.0209
## Feb 1961       418.4127 320.1675 516.6578
## Mar 1961       475.6417 377.3965 573.8869
## Apr 1961       472.5972 374.3520 570.8423
## May 1961       485.9002 387.6551 584.1454
## Jun 1961       563.4605 465.2154 661.7057
## Jul 1961       632.3409 534.0957 730.5860
## Aug 1961       627.7536 529.5084 725.9987
## Sep 1961       532.9010 434.6559 631.1462
## Oct 1961       463.0072 364.7621 561.2524
## Nov 1961       403.4354 305.1902 501.6805
## Dec 1961       449.5905 351.3453 547.8356
## Jan 1962       460.2839 362.0387 558.5290
## Feb 1962       433.9292 335.6841 532.1744
## Mar 1962       493.2262 394.9810 591.4713
## Apr 1962       490.0154 391.7703 588.2606
## May 1962       503.7540 405.5088 601.9991
## Jun 1962       584.1009 485.8558 682.3461
## Jul 1962       655.4339 557.1888 753.6791
## Aug 1962       650.6096 552.3644 748.8547
## Sep 1962       552.2448 453.9997 650.4900
## Oct 1962       479.7632 381.5181 578.0084
## Nov 1962       417.9916 319.7465 516.2368
## Dec 1962       465.7634 367.5183 564.0086
## Jan 1963       476.7920 378.5468 575.0371
plot(obj)

#(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=rvfl::rvfl, attention=FALSE)))
#plot(obj)
(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=stats::lm, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.7666 345.3856 542.1477
## Feb 1961       418.3980 320.0170 516.7791
## Mar 1961       475.6182 377.2371 573.9992
## Apr 1961       472.5670 374.1859 570.9481
## May 1961       485.8623 387.4812 584.2433
## Jun 1961       563.4085 465.0275 661.7896
## Jul 1961       632.2736 533.8925 730.6546
## Aug 1961       627.6780 529.2969 726.0590
## Sep 1961       532.8294 434.4483 631.2105
## Oct 1961       462.9386 364.5575 561.3196
## Nov 1961       403.3700 304.9890 501.7511
## Dec 1961       449.5115 351.1304 547.8926
## Jan 1962       460.1967 361.8157 558.5778
## Feb 1962       433.8412 335.4601 532.2223
## Mar 1962       493.1195 394.7385 591.5006
## Apr 1962       489.9029 391.5219 588.2840
## May 1962       503.6316 405.2506 602.0127
## Jun 1962       583.9514 485.5703 682.3324
## Jul 1962       655.2575 556.8764 753.6386
## Aug 1962       650.4259 552.0448 748.8070
## Sep 1962       552.0818 453.7007 650.4628
## Oct 1962       479.6154 381.2344 577.9965
## Nov 1962       417.8575 319.4764 516.2386
## Dec 1962       465.6080 367.2269 563.9891
## Jan 1963       476.6268 378.2458 575.0079
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=MASS::lqs, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.8060 345.8756 541.7365
## Feb 1961       418.4615 320.5311 516.3920
## Mar 1961       475.7201 377.7897 573.6506
## Apr 1961       472.6978 374.7673 570.6282
## May 1961       486.0268 388.0963 583.9572
## Jun 1961       563.6340 465.7035 661.5644
## Jul 1961       632.5652 534.6347 730.4956
## Aug 1961       628.0056 530.0752 725.9361
## Sep 1961       533.1397 435.2093 631.0702
## Oct 1961       463.2360 365.3055 561.1664
## Nov 1961       403.6533 305.7228 501.5837
## Dec 1961       449.8538 351.9233 547.7842
## Jan 1962       460.5743 362.6438 558.5047
## Feb 1962       434.2226 336.2921 532.1530
## Mar 1962       493.5818 395.6513 591.5122
## Apr 1962       490.3905 392.4601 588.3210
## May 1962       504.1619 406.2314 602.0923
## Jun 1962       584.5996 486.6692 682.5301
## Jul 1962       656.0222 558.0918 753.9527
## Aug 1962       651.2218 553.2913 749.1522
## Sep 1962       552.7884 454.8579 650.7188
## Oct 1962       480.2561 382.3256 578.1865
## Nov 1962       418.4389 320.5085 516.3694
## Dec 1962       466.2816 368.3512 564.2121
## Jan 1963       477.3426 379.4121 575.2730
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=gam::gam, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.7666 345.3856 542.1477
## Feb 1961       418.3980 320.0170 516.7791
## Mar 1961       475.6182 377.2371 573.9992
## Apr 1961       472.5670 374.1859 570.9481
## May 1961       485.8623 387.4812 584.2433
## Jun 1961       563.4085 465.0275 661.7896
## Jul 1961       632.2736 533.8925 730.6546
## Aug 1961       627.6780 529.2969 726.0590
## Sep 1961       532.8294 434.4483 631.2105
## Oct 1961       462.9386 364.5575 561.3196
## Nov 1961       403.3700 304.9890 501.7511
## Dec 1961       449.5115 351.1304 547.8926
## Jan 1962       460.1967 361.8157 558.5778
## Feb 1962       433.8412 335.4601 532.2223
## Mar 1962       493.1195 394.7385 591.5006
## Apr 1962       489.9029 391.5219 588.2840
## May 1962       503.6316 405.2506 602.0127
## Jun 1962       583.9514 485.5703 682.3324
## Jul 1962       655.2575 556.8764 753.6386
## Aug 1962       650.4259 552.0448 748.8070
## Sep 1962       552.0818 453.7007 650.4628
## Oct 1962       479.6154 381.2344 577.9965
## Nov 1962       417.8575 319.4764 516.2386
## Dec 1962       465.6080 367.2269 563.9891
## Jan 1963       476.6268 378.2458 575.0079
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=quantreg::rq, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       443.8071 345.7476 541.8667
## Feb 1961       418.4633 320.4037 516.5228
## Mar 1961       475.7230 377.6634 573.7825
## Apr 1961       472.7014 374.6418 570.7609
## May 1961       486.0314 387.9718 584.0909
## Jun 1961       563.6402 465.5807 661.6998
## Jul 1961       632.5733 534.5138 730.6329
## Aug 1961       628.0147 529.9552 726.0743
## Sep 1961       533.1484 435.0888 631.2079
## Oct 1961       463.2443 365.1847 561.3038
## Nov 1961       403.6612 305.6016 501.7207
## Dec 1961       449.8633 351.8038 547.9229
## Jan 1962       460.5848 362.5253 558.6444
## Feb 1962       434.2332 336.1737 532.2928
## Mar 1962       493.5946 395.5351 591.6542
## Apr 1962       490.4041 392.3446 588.4637
## May 1962       504.1767 406.1171 602.2362
## Jun 1962       584.6177 486.5581 682.6772
## Jul 1962       656.0435 557.9840 754.1031
## Aug 1962       651.2440 553.1844 749.3035
## Sep 1962       552.8081 454.7485 650.8676
## Oct 1962       480.2740 382.2144 578.3335
## Nov 1962       418.4551 320.3956 516.5147
## Dec 1962       466.3004 368.2408 564.3599
## Jan 1963       477.3625 379.3030 575.4221
plot(obj)