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On minimax sequential procedures for exponential families of stochastic processes
Applicationes Mathematicae, Tome 25 (1999) no. 1, pp. 1-18
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The problem of finding minimax sequential estimation procedures for stochastic processes is considered. It is assumed that in addition to the loss associated with the error of estimation a cost of observing the process is incurred. A class of minimax sequential procedures is derived explicitly for a one-parameter exponential family of stochastic processes. The minimax sequential procedures are presented in some special models, in particular, for estimating a parameter of exponential families of diffusions, for estimating the mean or drift coefficients of the class of Ornstein-Uhlenbeck processes, for estimating the drift of a geometric Brownian motion and for estimating a parameter of a family of counting processes. A class of minimax sequential rules for a compound Poisson process with multinomial jumps is also found.
DOI : 10.4064/am-25-1-1-18
Keywords: Bayes sequential estimation, minimax sequential procedure, exponential family of processes, stopping time, sequential decision procedure 
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Ryszard Magiera. On minimax sequential procedures for exponential families of stochastic processes. Applicationes Mathematicae, Tome 25 (1999) no. 1, pp. 1-18. doi: 10.4064/am-25-1-1-18

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