CONCENTRATION INEQUALITIES FOR DEPENDENT RANDOM VARIABLES VIA THE MARTINGALE METHOD

被引:90
作者
Kontorovich, Leonid [1 ]
Ramanan, Kavita [2 ]
机构
[1] Weizmann Inst Sci, Dept Math, IL-76100 Rehovot, Israel
[2] Carnegie Mellon Univ, Dept Math Sci, Pittsburgh, PA 15213 USA
关键词
Concentration inequality; McDiarmid's bound; bounded martingale differences; Markov chains; contracting Markov chains; hidden Markov chains; mixing coefficients;
D O I
10.1214/07-AOP384
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The martingale method is used to establish concentration inequalities for a class of dependent random sequences on a countable state space, with the constants in the inequalities expressed in terms of certain mixing coefficients. Along the way, bounds are obtained oil martingale differences associated with the random sequences, which may be of independent interest. As applications of the main result, concentration inequalities are also derived for inhomogeneous Markov chains and hidden Markov chains, and ail external property associated with their martingale difference bounds is established. This work complements and generalizes certain concentration inequalities obtained by Marton and Samson, while also providing different proofs of some known results.
引用
收藏
页码:2126 / 2158
页数:33
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