Large deviation lower bounds for arbitrary additive functionals of a Markov chain

• 成果类型: Article
• 署名作者: de Acosta, A; Ney, P
• 署名单位: University System of Ohio; Case Western Reserve University; University of Wisconsin System; University of Wisconsin Madison
• 刊物名称: ANNALS OF PROBABILITY
• ISSN/ISSBN: 0091-1798
• 发表日期: 1998
• 页码: 1660-1682
• 关键词: asymptotic evaluation; process expectations; large time; random vectors

摘要

A universal large deviation lower bound is proved for sums of Banach space valued functions of an irreducible, general state space Markov chain. There are no restrictions on the functions (other than measurability).