Aryeh Kontorovich

Senior Academic

Concentration inequalities for dependent random variables via the martingale method

Leonid Kontorovich, Kavita Ramanan

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 on 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 inhomoge-neous Markov chains and hidden Markov chains, and an extremal 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.

Publication language English
Pages 2126-2158
Journal Annals of Probability
Volume 36
Issue number 6
Publication status Published - 01.11.2008

Keywords

Bounded martingale differences
Concentration inequality
Contracting markov chains
Hidden markov chains
Markov chains
McDiarmid's bound
Mixing coefficients

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Access to Document
10.1214/07-AOP384
Other files and links
Link to publication in Scopus