An Efficient Jackknife Model Averaging Method

Published Online:https://doi.org/10.1287/ijoc.2024.0946

References

  • Akaike H (1973) Information theory and an extension of the maximum likelihood principle. Petrov B, Caski F, eds. Second International Symposium on Information Theory (Akademiai Kiado, Budapest).Google Scholar
  • Ando T, Li KC (2014) A model-averaging approach for high-dimensional regression. J. Amer. Statist. Assoc. 109(505):254–265.CrossrefGoogle Scholar
  • Ando T, Li KC (2017) A weight-relaxed model averaging approach for high-dimensional generalized linear models. Ann. Statist. 45(6):2654–2679.CrossrefGoogle Scholar
  • Beirami A, Razaviyayn M, Shahrampour S, Tarokh V (2017) On optimal generalizability in parametric learning. Proc. 31st Internat. Conf. Neural Inform. Processing Systems, vol. 30 (Curran Associates Inc., Red Hook, NY), 3458–3468.Google Scholar
  • Chen Z, Liao J, Xu W (2026) An efficient jackknife model averaging method. https://doi.org/10.1287/ijoc.2024.0946.cd, https://github.com/INFORMSJoC/2024.0946.Google Scholar
  • Chen Z, Liao J, Xu W, Yang Y (2023) Multifold cross-validation model averaging for generalized additive partial linear models. J. Comput. Graph. Statist. 32(4):1649–1659.CrossrefGoogle Scholar
  • Debruyne M, Hubert M, Suykens J (2008) Model selection in kernel based regression using the influence function. J. Machine Learn. Res. 9:2377–2400.Google Scholar
  • Draper D (1995) Assessment and propagation of model uncertainty. J. Roy. Statist. Soc. Ser. B. 57(1):45–70.CrossrefGoogle Scholar
  • Feng Z, He B, Xie T, Zhang X, Zong X (2024) Ranking model averaging: Ranking based on model averaging. INFORMS J. Comput. 37(3):703–722.CrossrefGoogle Scholar
  • Hansen BE, Racine J (2012) Jackknife model averaging. J. Econom. 167(1):38–46.CrossrefGoogle Scholar
  • Hoeting JA, Madigan D, Raftery AE, Volinsky CT (1999) Bayesian model averaging: A tutorial. Statist. Sci. 14(4):382–401.CrossrefGoogle Scholar
  • Hsu CW, Lin CJ (2002) A comparison of methods for multiclass support vector machines. IEEE Trans. Neural Networks 13(2):415–425.CrossrefGoogle Scholar
  • Kirkby JL, Nguyen DH, Nguyen D, Nguyen NN (2022) Inversion-free subsampling Newton’s method for large sample logistic regression. Statist. Papers 63:943–963.CrossrefGoogle Scholar
  • Krueger T, Panknin D, Braun M (2015) Fast cross-validation via sequential testing. J. Machine Learn. Res. 16:1103–1155.Google Scholar
  • Li KC (1987) Asymptotic optimality for Cp, CL, cross-validation and generalized cross-validation: Discrete index set. Ann. Statist. 15(3):958–975.CrossrefGoogle Scholar
  • Li J, Lv J, Wan ATK, Liao J (2022) Adaboost semiparametric model averaging prediction for multiple categories. J. Amer. Statist. Assoc. 117(537):495–509.CrossrefGoogle Scholar
  • Liao J, Zong X, Zhang X, Zou G (2019) Model averaging based on leave-subject-out cross-validation for vector autoregressions. J. Econom. 209(1):35–60. CrossrefGoogle Scholar
  • Liu Y, Liao S, Jiang S, Ding L, Lin H, Wang W (2020) Fast cross-validation for kernel-based algorithms. IEEE Trans. Pattern Anal. Machine Intelligence 42(5):1083–1096.Google Scholar
  • Lu X, Su L (2015) Jackknife model averaging for quantile regressions. J. Econom. 188(1):40–58.CrossrefGoogle Scholar
  • Nelson BL, Wan ATK, Zou G, Zhang X, Jiang X (2020) Reducing simulation input-model risk via input model averaging. INFORMS J. Comput. 33(2):672–684.Google Scholar
  • Rad KR, Maleki A (2020) A scalable estimate of the out-of-sample prediction error via approximate leave-one-out cross-validation. J. Roy. Statist. Soc. Ser. B. 82(4):965–996.CrossrefGoogle Scholar
  • Schwarz G (1978) Estimating the dimension of a model. Ann. Statist. 6(2):461–464.CrossrefGoogle Scholar
  • Sun Y, Hong Y, Wang S, Zhang X (2023) Penalized time-varying model averaging. J. Econom. 235(2):1355–1377.CrossrefGoogle Scholar
  • Sun Y, Zhang X, Wan ATK, Wang S (2022) Model averaging for interval-valued data. Eur. J. Oper. Res. 301(2):772–784.CrossrefGoogle Scholar
  • Székely GJ, Rizzo ML, Bakirov NK (2007) Measuring and testing dependence by correlation of distances. Ann. Statist. 35(6):2769–2794.CrossrefGoogle Scholar
  • Wang S, Zhou W, Lu H, Maleki A, Mirrokni V (2018) Approximate leave-one-out for fast parameter tuning in high dimensions. Proc. 35th Internat. Conf. Machine Learn., vol. 80 (PMLR, New York).Google Scholar
  • Wang M, Zhang X, Wan ATK, Zou G, You K (2023) Jackknife model averaging for high-dimensional quantile regression. Biometrics 79(1):178–189.CrossrefGoogle Scholar
  • Wilson A, Kasy M, Mackey L (2020) Approximate cross-validation: Guarantees for model assessment and selection. Internat. Conf. Artificial Intelligence Statist., vol. 108 (PMLR, New York).Google Scholar
  • Xu G, Huang JZ (2012) Asymptotic optimality and efficient computation of the leave-subject-out cross-validation. Ann. Statist. 40(6):3003–3030.CrossrefGoogle Scholar
  • Yu D, Zhang X, Liang H (2025) Unified optimal model averaging with a general loss function based on cross-validation. J. Amer. Statist. Assoc. 120(552):2697–2708.Google Scholar
  • Yuan Z, Yang Y (2005) Combining linear regression models: When and how? J. Amer. Statist. Assoc. 100(472):1202–1214.CrossrefGoogle Scholar
  • Zhan Z, Yang Y (2022) Profile electoral college cross-validation. Inform. Sci. 586:24–40.CrossrefGoogle Scholar
  • Zhang X, Liu CA (2023) Model averaging prediction by K-fold cross-validation. J. Econom. 235(1):280–301.CrossrefGoogle Scholar
  • Zhang X, Liu H, Wei Y, Ma Y (2024) Prediction using many samples with models possibly containing partially shared parameters. J. Bus. Econom. Statist. 42(1):187–196.CrossrefGoogle Scholar
  • Zhang X, Yu D, Zou G, Liang H (2016) Optimal model averaging estimation for generalized linear models and generalized linear mixed-effects models. J. Amer. Statist. Assoc. 111(516):1175–1790.CrossrefGoogle Scholar
  • Zhang X, Zou G, Liang H, Carroll RJ (2020) Parsimonious model averaging with a diverging number of parameters. J. Amer. Statist. Assoc. 115(530):972–984.CrossrefGoogle Scholar
  • Zou J, Wang W, Zhang X, Zou G (2022) Optimal model averaging for divergent-dimensional Poisson regressions. Econom. Rev. 41(7):775–805.CrossrefGoogle Scholar
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