The first account in book form of all the essential features of the quasi-likelihood methodology, stressing its value as a general purpose inferential tool. The treatment is rather informal, emphasizing essential principles rather than detailed proofs, and readers are assumed to have a firm grounding in probability and statistics at the graduate level. Many examples of the use of the methods in both classical statistical and stochastic process contexts are provided.

Contenuti:

The General Framework.- An Alternative Approach: E-Sufficiency.- Asymptotic Confidence Zones of Minimum Size.- Asymptotic Quasi-Likelihood.- Combining Estimating Functions.- Projected Quasi-Likelihood.- Bypassing the Likelihood.- Hypothesis Testing.- Infinite Dimensional Problems.- Miscellaneous Applications.- Consistency and Asymptotic Normality for Estimating Functions.- Complements and Strategies for Application.

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