A class of stopping rules for fixed precision sequential estimates
A class of unbiased kernel estimates of a probability density function
We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.
A Continuous-Time Sequential Testing Problem.
A direct method of computation of the characteristics for SPRTs in the case of discrete random variables
A discrete theory of search. I
A discrete theory of search. II
A functional central limit theorem for martingales in C(K) and its application to sequential estimates.
A Less Sensitive Linear Detector for the Change Point Based on Kernel Smoothing Method.
A method of detecting changes in the behaviour of locally stationary sequences
A modification of Sudakov's lemma and efficient sequential plans for some jump Markov processes
A modification of Sudakov's lemma and efficient sequential plans for the Ornstein-Uhlenbeck process
A New Sequential Design Based on the Robbins-Monro Procedure.
A note on a selection problem
A Note On A Sequential Probability Ratio Test.
A note on confidence intervals for the Kiefer-Wolfowitz problem
A note on exponentially bounded stopping times of certain one-sample sequential rank order tests.
A note on selecting the better binomial population.
A Note on Three-Stage Confidence Intervals for the Difference of Locations: The Exponential Case.
A penalized bandit algorithm.
A sequential Bayesian approach to estimating the dimension of a multinomial distribution