Stability and other limit laws for exit times of random walks from a strip or a halfplane
Stability estimating in optimal sequential hypotheses testing
We study the stability of the classical optimal sequential probability ratio test based on independent identically distributed observations when testing two simple hypotheses about their common density : versus . As a functional to be minimized, it is used a weighted sum of the average (under ) sample number and the two types error probabilities. We prove that the problem is reduced to stopping time optimization for a ratio process generated by with the density . For being the corresponding...
Statistical Inference about the Drift Parameter in Stochastic Processes
In statistical inference on the drift parameter in the Wiener process with a constant drift there is a large number of options how to do it. We may, for example, base this inference on the properties of the standard normal distribution applied to the differences between the observed values of the process at discrete times. Although such methods are very simple, it turns out that more appropriate is to use the sequential methods. For the hypotheses testing about the drift parameter it is more...
Stetige stochastische Approximation.
Stochastic approximations in the presence of trend
Stochastic approximations of the solution of a full Boltzmann equation with small initial data
Stochastic approximations of the solution of a full Boltzmann equation with small initial data
This paper gives an approximation of the solution of the Boltzmann equation by stochastic interacting particle systems in a case of cut-off collision operator and small initial data. In this case, following the ideas of Mischler and Perthame, we prove the existence and uniqueness of the solution of this equation and also the existence and uniqueness of the solution of the associated nonlinear martingale problem. Then, we first delocalize the interaction by considering a mollified Boltzmann...
Stopping problems as special statistical decision problems
Sufficiency in sequential experimental design problems
Sur quelques algorithmes récursifs pour les probabilités numériques
The aim of this paper is to take an in-depth look at the long time behaviour of some continuous time markovian dynamical systems and at its numerical analysis. We first propose a short overview of the main ergodicity properties of time continuous homogeneous Markov processes (stability, positive recurrence). The basic tool is a Lyapunov function. Then, we investigate if these properties still hold for the time discretization of these processes, either with constant or decreasing step (ODE method...
Sur quelques algorithmes récursifs pour les probabilités numériques
The aim of this paper is to take an in-depth look at the long time behaviour of some continuous time Markovian dynamical systems and at its numerical analysis. We first propose a short overview of the main ergodicity properties of time continuous homogeneous Markov processes (stability, positive recurrence). The basic tool is a Lyapunov function. Then, we investigate if these properties still hold for the time discretization of these processes, either with constant or decreasing step (ODE...
Sur quelques résultats asymptotiques pour le processus de Robbins-Monro
The Bayes choice of an experiment in estimating a success probability
A Bayesian method of estimation of a success probability p is considered in the case when two experiments are available: individual Bernoulli (p) trials-the p-experiment-or products of r individual Bernoulli (p) trials-the -experiment. This problem has its roots in reliability, where one can test either single components or a system of r identical components. One of the problems considered is to find the degree r̃ of the -experiment and the size m̃ of the p-experiment such that the Bayes estimator...
The Bayes sequential estimation of a normal mean from delayed observations
The problem of estimating the mean of a normal distribution is considered in the special case when the data arrive at random times. Certain classes of Bayes sequential estimation procedures are derived under LINEX and reflected normal loss function and with the observation cost determined by a function of the stopping time and the number of observations up to this time.
The Bayesian sequential model with the range-based probability estimation
The characterization of efficient sequential plans for the Ornstein-Uhlenbeck velocity process
The Combined Inverse Binomial Sampling Procedure.
The continuous dynamic Robbins-Monro procedure
The N-Armed Bandit with Unimodal Structure.
The optimum sequential test of a finite number of hypotheses for statistically dependent observations