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Discusses the asymptotic theory of semimartingales needed for researchers working in the area of statistical inference for stochastic processes. This book covers topics that include: asymptotic likelihood theory, quasi-likelihood, likelihood and efficiency, inference for counting processes, and inference for semimartingale regression models.
This book gives a comprehensive review of results for associated sequences and demimartingales developed so far, with special emphasis on demimartingales and related processes. Probabilistic properties of associated sequences, demimartingales and related processes are discussed in the first six chapters. Applications of some of these results to some problems in nonparametric statistical inference for such processes are investigated in the last three chapters.
Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question.
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