Asymptotically optimal sequential discrimination between Markov chains

被引:0
|
作者
Malyutov, MB [1 ]
Tsitovich, II [1 ]
机构
[1] Northeastern Univ, Dept Math, Boston, MA 02115 USA
关键词
controlled Markov chain; sequential test; second order optimality; mean length of a strategy;
D O I
暂无
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
An asymptotic lower bound is derived involving a second additive term of order root /ln alpha/ as alpha --> 0 for the mean length of a sequential strategy 3 for discrimination between two statistical models for Markov chains. The parameter alpha is the maximal error probability of s. A sequential strategy is outlined attaining (or almost attaining) this asymptotic bound uniformly over the distributions of models including those from the indifference zone.
引用
收藏
页码:163 / 170
页数:8
相关论文
共 50 条