General Exponential Models for Discrete Observations
STANFORD UNIV CA DEPT OF STATISTICS
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A class of models generalizing exponential families is defined via the algebraic structure of the sufficient statistics. The maximum likelihood estimate for the unknown parameter is shown to exist and be unique. The sequence of sufficient statistics from successive repetitions of experiments corresponding to a general exponential model is shown to form an extreme family of Markov chains as defined by Lauritzen 1974.
- Statistics and Probability