# Elastic Net 
(res1 <- ahead::mlf(USAccDeaths, fit_func = glmnet::cv.glmnet, h=25L, lags=15L, 
type_pi="kde", B=250L))
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
## Warning: Option grouped=FALSE enforced in cv.glmnet, since < 3 observations per
## fold
## Warning: Option grouped=FALSE enforced in cv.glmnet, since < 3 observations per
## fold
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8213.602 6651.349 10022.678
## Feb 1979       7363.028 5825.251  9023.169
## Mar 1979       8046.157 6617.970  9972.950
## Apr 1979       8424.551 6851.056 10079.520
## May 1979       9250.309 7742.602 11244.938
## Jun 1979       9632.789 8054.901 11510.649
## Jul 1979      10371.590 8766.785 12112.602
## Aug 1979       9964.858 8490.399 11752.339
## Sep 1979       9300.171 7678.672 11155.126
## Oct 1979       9208.652 7485.371 10838.584
## Nov 1979       8844.666 7278.118 10374.782
## Dec 1979       9439.201 7624.087 11337.581
## Jan 1980       8494.563 7242.219 10293.563
## Feb 1980       7768.356 6158.841  9755.492
## Mar 1980       8447.580 6973.770 10510.269
## Apr 1980       8686.358 6964.017 10711.646
## May 1980       9424.350 7760.944 11171.701
## Jun 1980       9755.722 8089.406 11644.557
## Jul 1980      10480.731 9360.777 12447.682
## Aug 1980      10037.390 8340.691 11994.056
## Sep 1980       9445.844 7803.507 11374.375
## Oct 1980       9396.013 7840.971 11184.159
## Nov 1980       9233.782 7451.326 10947.589
## Dec 1980       9445.088 7840.768 11157.442
## Jan 1981       8649.000 6996.512 10370.505
(res2 <- ahead::mlf(AirPassengers, fit_func = glmnet::cv.glmnet, h=25L, lags=15L, 
type_pi="kde", B=250L))
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       459.7552 380.0345 606.7475
## Feb 1961       430.9401 359.5434 547.3340
## Mar 1961       453.5584 381.8397 587.8587
## Apr 1961       500.1141 422.7564 661.4820
## May 1961       527.4440 448.6997 650.1500
## Jun 1961       587.2034 510.6481 737.4635
## Jul 1961       676.5792 602.9565 812.6947
## Aug 1961       663.5441 588.0662 793.0042
## Sep 1961       561.2717 479.7528 701.3720
## Oct 1961       503.4956 426.6916 629.5803
## Nov 1961       434.2601 364.4169 559.5272
## Dec 1961       465.6561 383.2880 599.3938
## Jan 1962       491.7691 418.2933 622.8430
## Feb 1962       469.6840 395.7880 608.7285
## Mar 1962       487.1450 414.4287 598.2497
## Apr 1962       535.7208 467.2408 654.8935
## May 1962       565.6261 485.1066 683.0617
## Jun 1962       636.2178 569.5508 773.3438
## Jul 1962       732.1846 660.2531 845.8855
## Aug 1962       719.2072 645.9557 839.5347
## Sep 1962       619.9854 542.7392 757.1536
## Oct 1962       539.9768 464.6287 664.3884
## Nov 1962       476.9676 407.7306 608.2608
## Dec 1962       498.3800 428.1434 658.1620
## Jan 1963       527.7314 448.3584 685.2382
par(mfrow=c(1, 2))
plot(res1)
plot(res2)

# SVM
(res3 <- ahead::mlf(USAccDeaths, fit_func = e1071::svm, h=25L, lags=15L, 
type_pi="kde", B=250L)) 
##          Point Forecast    Lo 95     Hi 95
## Jan 1979       8199.674 6473.090  9969.367
## Feb 1979       7729.387 6114.349  9632.456
## Mar 1979       7792.193 6132.693  9821.170
## Apr 1979       8192.800 6448.504 10084.277
## May 1979       8829.029 7247.419 10818.663
## Jun 1979       9401.282 7554.712 11260.581
## Jul 1979       9962.968 8359.314 11814.882
## Aug 1979       9748.157 8005.109 11577.599
## Sep 1979       9388.119 7739.654 11305.827
## Oct 1979       9136.904 7200.491 10908.398
## Nov 1979       8821.085 7242.572 10445.693
## Dec 1979       9068.206 6963.608 11055.792
## Jan 1980       8340.255 6799.574 10256.971
## Feb 1980       8023.531 6147.344  9887.678
## Mar 1980       7968.533 6055.050  9964.622
## Apr 1980       8048.986 6282.612 10044.950
## May 1980       8714.224 6868.880 10491.411
## Jun 1980       9318.806 7359.968 11252.699
## Jul 1980       9952.219 8386.563 11808.094
## Aug 1980       9875.771 8023.109 11831.048
## Sep 1980       9548.459 7838.888 11493.556
## Oct 1980       9177.084 7572.946 10941.686
## Nov 1980       9223.650 7294.213 11107.748
## Dec 1980       8914.639 7230.070 10721.664
## Jan 1981       8443.229 6608.354 10475.302
(res4 <- ahead::mlf(AirPassengers, fit_func = e1071::svm, h=25L, lags=15L, 
type_pi="kde", B=250L)) 
##          Point Forecast    Lo 95    Hi 95
## Jan 1961       447.0467 300.1038 680.7571
## Feb 1961       425.1280 298.0689 634.4811
## Mar 1961       438.3497 309.5155 675.2856
## Apr 1961       462.6512 320.5670 705.4005
## May 1961       482.4335 336.2366 701.5527
## Jun 1961       502.7700 354.6733 725.9698
## Jul 1961       537.9357 409.1501 770.2478
## Aug 1961       535.3644 400.8080 754.6808
## Sep 1961       492.5919 355.9317 728.8254
## Oct 1961       468.8418 328.9083 696.4125
## Nov 1961       429.0261 296.0011 648.3337
## Dec 1961       442.9659 286.2605 671.6427
## Jan 1962       463.7218 319.3723 687.8484
## Feb 1962       461.1741 318.6205 690.3431
## Mar 1962       468.8124 332.0720 660.5847
## Apr 1962       488.7456 353.6587 691.0124
## May 1962       499.5541 376.7622 694.4943
## Jun 1962       520.0000 397.0829 755.7963
## Jul 1962       551.8753 416.0097 747.1827
## Aug 1962       534.3479 399.1492 732.5522
## Sep 1962       503.5217 369.1076 730.4971
## Oct 1962       466.1787 325.9431 672.3289
## Nov 1962       445.1387 312.2892 670.5696
## Dec 1962       450.0594 321.7213 699.8489
## Jan 1963       458.8569 311.9392 690.6282
par(mfrow=c(1, 2))
plot(res3)
plot(res4)