This important book in statistical theory by one of the leading experts in this area unifies the two two important approaches to statistical parameter estimation. It will be of interest to researchers and graduate students in both mathematical statistics and probability theory.

The first account in book form The author is one of the leading experts in this area

Inhalt
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.