Generalization error bounds for stationary autoregressive models

2011/03/04 by Daniel J. McDonald, Cosma Rohilla Shalizi, McDonald, Daniel J. +4
Computer Science · Engineering · Mathematics · #Control Systems and Identification #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistical Methods and Inference #cs.LG #stat.ML

paper · pdf · doi:10.48550/arxiv.1103.0942

10 pages, 3 figures. CMU Statistics Technical Report

openalex publication_date 2011/03/04 · arxiv created 2011/06/03 · arxiv updated 2011/06/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We derive generalization error bounds for stationary univariate autoregressive (AR) models. We show that imposing stationarity is enough to control the Gaussian complexity without further regularization. This lets us use structural risk minimization for model selection. We demonstrate our methods by predicting interest rate movements.

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