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       8280.318  7768.626  8792.009
## Feb 1979       7522.491  6938.091  8106.890
## Mar 1979       8342.520  7693.508  8991.532
## Apr 1979       8580.623  7872.872  9288.374
## May 1979       9485.447  8723.472 10247.421
## Jun 1979       9914.243  9101.655 10726.831
## Jul 1979      10876.988 10016.759 11737.216
## Aug 1979      10149.192  9243.826 11054.559
## Sep 1979       9001.069  8052.712  9949.427
## Oct 1979       9394.424  8404.942 10383.907
## Nov 1979       8845.917  7816.951  9874.882
## Dec 1979       9065.254  7998.266 10132.243
## Jan 1980       8280.311  7176.608  9384.013
## Feb 1980       7522.484  6383.251  8661.718
## Mar 1980       8342.513  7168.823  9516.202
## Apr 1980       8580.616  7373.453  9787.778
## May 1980       9485.439  8245.707 10725.171
## Jun 1980       9914.235  8642.767 11185.702
## Jul 1980      10876.978  9574.548 12179.408
## Aug 1980      10149.184  8816.511 11481.857
## Sep 1980       9001.062  7638.816 10363.307
## Oct 1980       9394.416  8003.227 10785.605
## Nov 1980       8845.909  7426.367 10265.452
## Dec 1980       9065.246  7617.906 10512.587
## Jan 1981       8280.304  6805.689  9754.919
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=stats::glm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8270.694 7759.002  8782.385
## Feb 1979       7508.924 6924.525  8093.323
## Mar 1979       8322.125 7673.113  8971.137
## Apr 1979       8554.144 7846.393  9261.894
## May 1979       9450.093 8688.118 10212.067
## Jun 1979       9870.934 9058.346 10683.522
## Jul 1979      10822.498 9962.269 11682.726
## Aug 1979      10091.841 9186.475 10997.207
## Sep 1979       8944.434 7996.076  9892.791
## Oct 1979       9329.290 8339.807 10318.772
## Nov 1979       8778.913 7749.947  9807.878
## Dec 1979       8990.776 7923.787 10057.764
## Jan 1980       8206.972 7103.270  9310.674
## Feb 1980       7451.034 6311.800  8590.267
## Mar 1980       8257.924 7084.235  9431.614
## Apr 1980       8488.111 7280.948  9695.273
## May 1980       9377.097 8137.365 10616.829
## Jun 1980       9794.638 8523.170 11066.105
## Jul 1980      10738.793 9436.363 12041.223
## Aug 1980      10013.737 8681.063 11346.410
## Sep 1980       8875.165 7512.920 10237.410
## Oct 1980       9256.994 7865.805 10648.183
## Nov 1980       8710.838 7291.296 10130.381
## Dec 1980       8921.013 7473.673 10368.354
## Jan 1981       8143.250 6668.635  9617.865
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=MASS::rlm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8270.536 7758.844  8782.227
## Feb 1979       7508.701 6924.302  8093.100
## Mar 1979       8321.790 7672.778  8970.802
## Apr 1979       8553.709 7845.958  9261.459
## May 1979       9449.513 8687.538 10211.487
## Jun 1979       9870.223 9057.635 10682.811
## Jul 1979      10821.603 9961.375 11681.832
## Aug 1979      10090.899 9185.533 10996.265
## Sep 1979       8943.504 7995.146  9891.861
## Oct 1979       9328.220 8338.738 10317.703
## Nov 1979       8777.813 7748.847  9806.779
## Dec 1979       8989.553 7922.565 10056.542
## Jan 1980       8205.768 7102.066  9309.470
## Feb 1980       7449.861 6310.628  8589.094
## Mar 1980       8256.536 7082.846  9430.225
## Apr 1980       8486.592 7279.430  9693.755
## May 1980       9375.318 8135.586 10615.050
## Jun 1980       9792.674 8521.207 11064.142
## Jul 1980      10736.525 9434.095 12038.955
## Aug 1980      10011.513 8678.840 11344.187
## Sep 1980       8873.098 7510.853 10235.344
## Oct 1980       9254.738 7863.549 10645.927
## Nov 1980       8708.621 7289.079 10128.163
## Dec 1980       8918.646 7471.305 10365.986
## Jan 1981       8141.000 6666.385  9615.615
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       8285.588  7773.896  8797.279
## Feb 1979       7529.920  6945.520  8114.319
## Mar 1979       8353.688  7704.676  9002.700
## Apr 1979       8595.122  7887.372  9302.873
## May 1979       9504.806  8742.831 10266.780
## Jun 1979       9937.958  9125.370 10750.546
## Jul 1979      10906.825 10046.596 11767.054
## Aug 1979      10180.597  9275.231 11085.963
## Sep 1979       9032.082  8083.724  9980.439
## Oct 1979       9430.090  8440.608 10419.573
## Nov 1979       8882.606  7853.641  9911.572
## Dec 1979       9106.037  8039.048 10173.025
## Jan 1980       8320.469  7216.767  9424.172
## Feb 1980       7561.609  6422.375  8700.842
## Mar 1980       8388.832  7215.142  9562.521
## Apr 1980       8631.269  7424.107  9838.432
## May 1980       9544.764  8305.032 10784.496
## Jun 1980       9979.723  8708.256 11251.191
## Jul 1980      10952.645  9650.215 12255.075
## Aug 1980      10223.351  8890.678 11556.025
## Sep 1980       9069.999  7707.754 10432.245
## Oct 1980       9469.665  8078.477 10860.854
## Nov 1980       8919.871  7500.328 10339.413
## Dec 1980       9144.225  7696.884 10591.566
## Jan 1981       8355.351  6880.736  9829.966
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=stats::lm, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8270.694 7759.002  8782.385
## Feb 1979       7508.924 6924.525  8093.323
## Mar 1979       8322.125 7673.113  8971.137
## Apr 1979       8554.144 7846.393  9261.894
## May 1979       9450.093 8688.118 10212.067
## Jun 1979       9870.934 9058.346 10683.522
## Jul 1979      10822.498 9962.269 11682.726
## Aug 1979      10091.841 9186.475 10997.207
## Sep 1979       8944.434 7996.076  9892.791
## Oct 1979       9329.290 8339.807 10318.772
## Nov 1979       8778.913 7749.947  9807.878
## Dec 1979       8990.776 7923.787 10057.764
## Jan 1980       8206.972 7103.270  9310.674
## Feb 1980       7451.034 6311.800  8590.267
## Mar 1980       8257.924 7084.235  9431.614
## Apr 1980       8488.111 7280.948  9695.273
## May 1980       9377.097 8137.365 10616.829
## Jun 1980       9794.638 8523.170 11066.105
## Jul 1980      10738.793 9436.363 12041.223
## Aug 1980      10013.737 8681.063 11346.410
## Sep 1980       8875.165 7512.920 10237.410
## Oct 1980       9256.994 7865.805 10648.183
## Nov 1980       8710.838 7291.296 10130.381
## Dec 1980       8921.013 7473.673 10368.354
## Jan 1981       8143.250 6668.635  9617.865
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=gam::gam, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8270.694 7759.002  8782.385
## Feb 1979       7508.924 6924.525  8093.323
## Mar 1979       8322.125 7673.113  8971.137
## Apr 1979       8554.144 7846.393  9261.894
## May 1979       9450.093 8688.118 10212.067
## Jun 1979       9870.934 9058.346 10683.522
## Jul 1979      10822.498 9962.269 11682.726
## Aug 1979      10091.841 9186.475 10997.207
## Sep 1979       8944.434 7996.076  9892.791
## Oct 1979       9329.290 8339.807 10318.772
## Nov 1979       8778.913 7749.947  9807.878
## Dec 1979       8990.776 7923.787 10057.764
## Jan 1980       8206.972 7103.270  9310.674
## Feb 1980       7451.034 6311.800  8590.267
## Mar 1980       8257.924 7084.235  9431.614
## Apr 1980       8488.111 7280.948  9695.273
## May 1980       9377.097 8137.365 10616.829
## Jun 1980       9794.638 8523.170 11066.105
## Jul 1980      10738.793 9436.363 12041.223
## Aug 1980      10013.737 8681.063 11346.410
## Sep 1980       8875.165 7512.920 10237.410
## Oct 1980       9256.994 7865.805 10648.183
## Nov 1980       8710.838 7291.296 10130.381
## Dec 1980       8921.013 7473.673 10368.354
## Jan 1981       8143.250 6668.635  9617.865
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(USAccDeaths, h=25L, fit_func=quantreg::rq, attention=FALSE)))
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8272.676 7760.984  8784.367
## Feb 1979       7511.718 6927.318  8096.117
## Mar 1979       8326.325 7677.313  8975.337
## Apr 1979       8559.596 7851.846  9267.347
## May 1979       9457.373 8695.399 10219.348
## Jun 1979       9879.852 9067.264 10692.440
## Jul 1979      10833.719 9973.490 11693.947
## Aug 1979      10103.651 9198.285 11009.017
## Sep 1979       8956.096 8007.739  9904.454
## Oct 1979       9342.702 8353.220 10332.185
## Nov 1979       8792.711 7763.745  9821.676
## Dec 1979       9006.113 7939.124 10073.101
## Jan 1980       8222.074 7118.372  9325.776
## Feb 1980       7465.747 6326.514  8604.981
## Mar 1980       8275.343 7101.654  9449.033
## Apr 1980       8507.160 7299.997  9714.322
## May 1980       9399.407 8159.675 10639.139
## Jun 1980       9819.266 8547.798 11090.733
## Jul 1980      10767.249 9464.819 12069.679
## Aug 1980      10041.629 8708.955 11374.302
## Sep 1980       8901.090 7538.845 10263.336
## Oct 1980       9285.293 7894.104 10676.482
## Nov 1980       8738.653 7319.110 10158.195
## Dec 1980       8950.715 7503.374 10398.055
## Jan 1981       8171.473 6696.858  9646.088
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       438.6460 417.5645 459.7274
## Feb 1961       425.8291 398.3275 453.3308
## Mar 1961       485.4662 452.7821 518.1504
## Apr 1961       470.3098 433.1592 507.4603
## May 1961       472.9516 431.8167 514.0865
## Jun 1961       536.2811 491.5151 581.0470
## Jul 1961       591.1210 542.9972 639.2449
## Aug 1961       587.9247 536.6625 639.1869
## Sep 1961       511.0994 456.8801 565.3186
## Oct 1961       444.2413 387.2181 501.2645
## Nov 1961       386.1320 326.4365 445.8275
## Dec 1961       433.1976 370.9443 495.4508
## Jan 1962       438.6992 373.9893 503.4092
## Feb 1962       425.8808 358.8041 492.9576
## Mar 1962       485.5252 416.1623 554.8880
## Apr 1962       470.3669 398.7909 541.9428
## May 1962       473.0091 399.2864 546.7317
## Jun 1962       536.3462 460.5376 612.1548
## Jul 1962       591.1928 513.3541 669.0314
## Aug 1962       587.9961 508.1790 667.8132
## Sep 1962       511.1614 429.4138 592.9091
## Oct 1962       444.2952 360.6615 527.9289
## Nov 1962       386.1789 300.7008 471.6570
## Dec 1962       433.2502 345.9666 520.5337
## Jan 1963       438.7525 349.7001 527.8049
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=stats::glm, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       440.0782 418.9967 461.1597
## Feb 1961       428.3843 400.8826 455.8859
## Mar 1961       489.7071 457.0229 522.3912
## Apr 1961       475.7046 438.5540 512.8552
## May 1961       479.6704 438.5355 520.8053
## Jun 1961       545.3663 500.6003 590.1322
## Jul 1961       602.7520 554.6282 650.8758
## Aug 1961       601.1008 549.8385 652.3630
## Sep 1961       523.9515 469.7322 578.1708
## Oct 1961       456.6271 399.6040 513.6503
## Nov 1961       397.9537 338.2582 457.6492
## Dec 1961       447.6449 385.3917 509.8982
## Jan 1962       454.5298 389.8198 519.2397
## Feb 1962       442.4135 375.3367 509.4902
## Mar 1962       505.7009 436.3380 575.0637
## Apr 1962       491.1989 419.6230 562.7749
## May 1962       495.2516 421.5289 568.9742
## Jun 1962       563.0336 487.2250 638.8422
## Jul 1962       622.2258 544.3872 700.0645
## Aug 1962       620.4691 540.6520 700.2862
## Sep 1962       540.7887 459.0411 622.5364
## Oct 1962       471.2617 387.6280 554.8954
## Nov 1962       410.6739 325.1958 496.1520
## Dec 1962       461.9154 374.6318 549.1989
## Jan 1963       468.9813 379.9289 558.0338
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=MASS::rlm, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       440.0750 418.9935 461.1565
## Feb 1961       428.3786 400.8770 455.8803
## Mar 1961       489.6977 457.0135 522.3818
## Apr 1961       475.6926 438.5421 512.8432
## May 1961       479.6555 438.5206 520.7904
## Jun 1961       545.3461 500.5801 590.1121
## Jul 1961       602.7262 554.6023 650.8500
## Aug 1961       601.0715 549.8093 652.3337
## Sep 1961       523.9230 469.7037 578.1422
## Oct 1961       456.5996 399.5765 513.6228
## Nov 1961       397.9275 338.2320 457.6230
## Dec 1961       447.6128 385.3596 509.8661
## Jan 1962       454.4946 389.7846 519.2046
## Feb 1962       442.3767 375.3000 509.4535
## Mar 1962       505.6561 436.2932 575.0189
## Apr 1962       491.1527 419.5767 562.7286
## May 1962       495.2022 421.4795 568.9248
## Jun 1962       562.9744 487.1658 638.7830
## Jul 1962       622.1569 544.3183 699.9956
## Aug 1962       620.3970 540.5799 700.2141
## Sep 1962       540.7230 458.9753 622.4706
## Oct 1962       471.2018 387.5682 554.8355
## Nov 1962       410.6195 325.1414 496.0976
## Dec 1962       461.8517 374.5682 549.1353
## Jan 1963       468.9142 379.8618 557.9666
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       440.0782 418.9967 461.1597
## Feb 1961       428.3843 400.8826 455.8859
## Mar 1961       489.7071 457.0229 522.3912
## Apr 1961       475.7046 438.5540 512.8552
## May 1961       479.6704 438.5355 520.8053
## Jun 1961       545.3663 500.6003 590.1322
## Jul 1961       602.7520 554.6282 650.8758
## Aug 1961       601.1008 549.8385 652.3630
## Sep 1961       523.9515 469.7322 578.1708
## Oct 1961       456.6271 399.6040 513.6503
## Nov 1961       397.9537 338.2582 457.6492
## Dec 1961       447.6449 385.3917 509.8982
## Jan 1962       454.5298 389.8198 519.2397
## Feb 1962       442.4135 375.3367 509.4902
## Mar 1962       505.7009 436.3380 575.0637
## Apr 1962       491.1989 419.6230 562.7749
## May 1962       495.2516 421.5289 568.9742
## Jun 1962       563.0336 487.2250 638.8422
## Jul 1962       622.2258 544.3872 700.0645
## Aug 1962       620.4691 540.6520 700.2862
## Sep 1962       540.7887 459.0411 622.5364
## Oct 1962       471.2617 387.6280 554.8954
## Nov 1962       410.6739 325.1958 496.1520
## Dec 1962       461.9154 374.6318 549.1989
## Jan 1963       468.9813 379.9289 558.0338
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=MASS::lqs, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       440.1306 419.0491 461.2121
## Feb 1961       428.4778 400.9761 455.9794
## Mar 1961       489.8622 457.1781 522.5464
## Apr 1961       475.9020 438.7514 513.0526
## May 1961       479.9162 438.7813 521.0511
## Jun 1961       545.6986 500.9327 590.4646
## Jul 1961       603.1775 555.0537 651.3013
## Aug 1961       601.5828 550.3206 652.8450
## Sep 1961       524.4217 470.2024 578.6409
## Oct 1961       457.0803 400.0571 514.1034
## Nov 1961       398.3862 338.6907 458.0817
## Dec 1961       448.1734 385.9202 510.4267
## Jan 1962       455.1089 390.3989 519.8189
## Feb 1962       443.0183 375.9415 510.0950
## Mar 1962       506.4390 437.0761 575.8018
## Apr 1962       491.9610 420.3851 563.5370
## May 1962       496.0653 422.3426 569.7879
## Jun 1962       564.0099 488.2014 639.8185
## Jul 1962       623.3611 545.5225 701.1998
## Aug 1962       621.6571 541.8400 701.4741
## Sep 1962       541.8726 460.1250 623.6203
## Oct 1962       472.2483 388.6146 555.8819
## Nov 1962       411.5700 326.0919 497.0481
## Dec 1962       462.9641 375.6805 550.2476
## Jan 1963       470.0872 381.0348 559.1396
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=gam::gam, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       440.0782 418.9967 461.1597
## Feb 1961       428.3843 400.8826 455.8859
## Mar 1961       489.7071 457.0229 522.3912
## Apr 1961       475.7046 438.5540 512.8552
## May 1961       479.6704 438.5355 520.8053
## Jun 1961       545.3663 500.6003 590.1322
## Jul 1961       602.7520 554.6282 650.8758
## Aug 1961       601.1008 549.8385 652.3630
## Sep 1961       523.9515 469.7322 578.1708
## Oct 1961       456.6271 399.6040 513.6503
## Nov 1961       397.9537 338.2582 457.6492
## Dec 1961       447.6449 385.3917 509.8982
## Jan 1962       454.5298 389.8198 519.2397
## Feb 1962       442.4135 375.3367 509.4902
## Mar 1962       505.7009 436.3380 575.0637
## Apr 1962       491.1989 419.6230 562.7749
## May 1962       495.2516 421.5289 568.9742
## Jun 1962       563.0336 487.2250 638.8422
## Jul 1962       622.2258 544.3872 700.0645
## Aug 1962       620.4691 540.6520 700.2862
## Sep 1962       540.7887 459.0411 622.5364
## Oct 1962       471.2617 387.6280 554.8954
## Nov 1962       410.6739 325.1958 496.1520
## Dec 1962       461.9154 374.6318 549.1989
## Jan 1963       468.9813 379.9289 558.0338
plot(obj)

(obj <- suppressWarnings(ahead::glmthetaf(AirPassengers, h=25L, fit_func=quantreg::rq, attention=FALSE)))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       440.0763 418.9948 461.1577
## Feb 1961       428.3808 400.8792 455.8825
## Mar 1961       489.7014 457.0172 522.3855
## Apr 1961       475.6973 438.5467 512.8479
## May 1961       479.6613 438.5264 520.7962
## Jun 1961       545.3540 500.5880 590.1199
## Jul 1961       602.7363 554.6124 650.8601
## Aug 1961       601.0829 549.8207 652.3452
## Sep 1961       523.9341 469.7148 578.1534
## Oct 1961       456.6104 399.5872 513.6336
## Nov 1961       397.9377 338.2422 457.6333
## Dec 1961       447.6254 385.3721 509.8786
## Jan 1962       454.5083 389.7984 519.2183
## Feb 1962       442.3911 375.3143 509.4678
## Mar 1962       505.6736 436.3107 575.0364
## Apr 1962       491.1707 419.5948 562.7467
## May 1962       495.2215 421.4988 568.9441
## Jun 1962       562.9975 487.1889 638.8061
## Jul 1962       622.1838 544.3452 700.0225
## Aug 1962       620.4251 540.6081 700.2422
## Sep 1962       540.7487 459.0010 622.4963
## Oct 1962       471.2252 387.5916 554.8589
## Nov 1962       410.6408 325.1627 496.1189
## Dec 1962       461.8766 374.5931 549.1602
## Jan 1963       468.9404 379.8880 557.9928
plot(obj)