The recursive identification problem in control and signal processing applications
The secretary problem : optimal selection with batch-interviewing and cost
The Sequential Probability Ratio Test Under Random Censorship.
The stability of parameter estimation of fuzzy variables
Recently, the parameter estimations for normal fuzzy variables in the Nahmias’ sense was studied by Cai [4]. These estimates were also studied for general -related, but not necessarily normal fuzzy variables by Hong [10] In this paper, we report on some properties of estimators that would appear to be desirable, including unbiasedness. We also consider asymptotic or “large-sample” properties of a particular type of estimator.
The "Thirty-seven Percent Rule" and the secretary problem with relative ranks
We revisit the problem of selecting an item from n choices that appear before us in random sequential order so as to minimize the expected rank of the item selected. In particular, we examine the stopping rule where we reject the first k items and then select the first subsequent item that ranks lower than the l-th lowest-ranked item among the first k. We prove that the optimal rule has k ~ n/e, as in the classical secretary problem where our sole objective is to select the item of lowest rank;...
Transitivity and approximate transitivity in problems of optimal stopping
Two-Stage Point Estimation with a Shrinkage Stopping Rule.
Un théorème d'itération stochastique multidimensionnelle
Uniform asymptotic normality for the Bernoulli scheme
It is easy to notice that no sequence of estimators of the probability of success θ in a Bernoulli scheme can converge (when standardized) to N(0,1) uniformly in θ ∈ ]0,1[. We show that the uniform asymptotic normality can be achieved if we allow the sample size, that is, the number of Bernoulli trials, to be chosen sequentially.
Using an Approximate Kiefer-Weiss Solution for Testing Insect Population Densities.
Γ-minimax sequential estimation for Markov-additive processes
The problem of estimating unknown parameters of Markov-additive processes from data observed up to a random stopping time is considered. To the problem of estimation, the intermediate approach between the Bayes and the minimax principle is applied in which it is assumed that a vague prior information on the distribution of the unknown parameters is available. The loss in estimating is assumed to consist of the error of estimation (defined by a weighted squared loss function) as well as a cost of...
Аппроксимация эмпирических полей, построенных по векторным наблюдениям с зависимыми координатами
Гарантийные процедуры статистического вывода (определение объема выборки)
Методы типа стохастической аппроксимации для решения линейных некорректных задач
О свойствах некоторых случайных процессов, возникающих в теории статистического оценивания
Об асимптотически оптимальном оценивании нуля неизвестной функции
Об асимптотической оптимальности биномиальных планов фиксированного объема в классе планов с ограниченной средней длиной траектории
Об односторонней сходимости модифицированного процесса Роббинса-Монро
Об условиях асимптотической эффективности рекуррентных оценок параметра сдвига.
Односторонняя сходимость непрерывных процессов стохастической аппроксимации