Let IIj (i= l,..., k) denote statistical populations (treatments, manufacturing processes, etc.)
specifkd respectively by univariate density functions f (x; 6’,.) with respect to some measure Y, …

By using information-theoretic bounds and sequential hypothesis testing theory, this paper
provides a new approach to optimal detection of abrupt changes in stochastic systems. This …

A class of simple adaptive allocation rules is proposed for the problem (often called the "multi-armed
bandit problem") of sampling x 1 , ⋯ x N sequentially from k populations with …

Strong consistency and asymptotic normality of least squares estimates in stochastic regression
models are established under certain weak assumptions on the stochastic regressors …

After a brief survey of a large variety of sequential detection procedures that are widely scattered
in statistical references on quality control and engineering references on fault detection …

The idea of writing this book arose in 2000 when the first author was assigned to teach the
required course STATS 240 (Statistical Methods in Finance) in the new MS program in …

We give a brief review of the developments in several classical problems of sequential
analysis and their applications to biomedicine, economics and engineering. Even though it can …

Stochastic approximation, introduced by Robbins and Monro in 1951, has become an
important and vibrant subject in optimization, control and signal processing. This paper reviews …

Self-normalized processes are of common occurrence in probabilistic and statistical studies.
A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is …

In this paper, we study analogues of the law of the iterated logarithm for delayed sums of
independent random variables. In the iid case, necessary and sufficient conditions for such …