students andpractitioners. Approximation Theorems of Mathematical Statisticscovers a broad range of limit theorems useful in mathematicalstatistics, along with methods of proof and techniques ofapplication. The manipulation of "probability" theorems to obtain"statistical" theorems is emphasized. Besides a knowledge of thesebasic statistical theorems, this lucid introduction to the subjectimparts an appreciation of the instrumental role of probabilitytheory.The book makes accessible to students and practicing professionalsin statistics, general mathematics, operations research, andengineering the essentials of:* The tools and foundations that are basic to asymptotic theory instatistics* The asymptotics of statistics computed from a sample, includingtransformations of vectors of more basic statistics, with emphasison asymptotic distribution theory and strong convergence* Important special classes of statistics, such as maximumlikelihood estimates and other asymptotic efficient procedures; W.Hoeffding's U-statistics and R. von Mises's "differentiablestatistical functions"* Statistics obtained as solutions of equations ("M-estimates"),linear functions of order statistics ("L-statistics"), and rankstatistics ("R-statistics")* Use of influence curves* Approaches toward asymptotic relative efficiency of statisticaltest procedures

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