Asymptotic Behavior of the Log-Likelihood Function in Stochastic Processes when Based on a Random Number of Random Variables

Author:

Roussas George G.,Bhattacharya Debasis

Publisher

Springer US

Reference12 articles.

1. Akritas, M.G. and Roussas, G.G. (1979). Asymptotic expansion of the log-likelihood function based on stopping times defined on a Markov process, Ann. Inst. Statist. Math., 31, 21–38.

2. Akritas, M.G., Roussas, G.G. and Stamatelos, G.D. (1984). Asymptotic expansion of the log-likelihood function based on stopping times defined on stochastic processes, Mathematical Structures - Computational Mathematics - Mathematical Modelling, 2, 90–96, Sofia.

3. Anscombe, F. J. (1952). Large sample theory of sequential estimation, Proc. Camb. Phil Soc., 48, 600–607.

4. Chow, Y.S. and Teicher, H (19..). Probability Theory, 3rd Ed., Springer-Verlag.

5. Le Cam, L. (1960). Locally asymptotically normal families of distributions, Univ. California Publ. Statist., 3, 37–98.

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