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演講公告

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Model Averaging Prediction for Possibly Nonstationary Autoregressions

  • 2024-10-16 (Wed.), 14:00 PM
  • 統計所B1演講廳;茶 會:13:40。
  • 實體與線上視訊同步進行。
  • Dr. Chu-An Liu ( 劉祝安 博士 )
  • 中央研究院經濟研究所

Abstract

As an alternative to model selection (MS), this paper considers model averaging (MA) for integrated autoregressive processes of infinite order. We derive a uniformly asymptotic expression for the mean squared prediction error (MSPE) of the averaging prediction with fixed weights and then propose a Mallows-type criterion to select the data-driven weights that minimize the MSPE asymptotically. We show that the proposed MA estimator and its variants, Shibata and Akaike MA estimators, are asymptotically optimal in the sense of achieving the lowest possible MSPE. We further demonstrate that MA can provide significant MSPE reduction over MS when the model misspecification bias is algebraic decay. These theoretical findings are extended to integrated AR models with deterministic time trends and are supported by Monte Carlo simulations and real data analysis.

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1131016 Dr. Chu-An Liu ( 劉祝安 博士 ).pdf
最後更新日期:2024-10-09 16:03
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