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Limit Theorems of Probability Theory: Sequences of Independent Random Variables (Oxford Studies in Probability, 4)

معرفی کتاب «Limit Theorems of Probability Theory: Sequences of Independent Random Variables (Oxford Studies in Probability, 4)» نوشتهٔ Petrov, Valentin Vladimirovič، منتشرشده توسط نشر Clarendon Press ; Oxford University Press در سال 1995. این کتاب در فرمت djvu، زبان انگلیسی ارائه شده است.

This book offers a superb overview of limit theorems and probability inequalities for sums of independent random variables. Unique in its combination of both classic and recent results, the book details the many practical aspects of these important tools for solving a great variety of problems in probability and statistics. Topics include limit theorems on convergence to infinitely divisible distributions, the central limit theorem with rates of convergence, the weak and strong law of large numbers, the law of the iterated logarithm, and the many inequalities for sums of an arbitrary number random variables. Ideal as both a graduate text and a reference for seasoned mathematicians, Limit Theorems of Probability Theory brings the reader to the frontier of current research. This book offers a superb overview of limit theorems and probability inequalities for sums of independent random variables. Unique in its combination of both classic and recent results, the book details the many practical aspects of these important tools for solving a great variety of problems in probability and statistics. Topics include limit theorems on convergence to infinitely divisible distributions, the central limit theorem with rates of convergence, the weak and strong law of large numbers, the law of the iterated logarithm, and the many inequalities for sums of an arbitrary number random variables. Ideal as both a graduate text and a reference for seasoned mathematicians, __Limit Theorems of Probability Theory__ brings the reader to the frontier of current research. Limit theorems and probability inequalities for sums of independent random variables are beneficial to those studying probability and statistics. This treatise presents a clear exposition of classical and modern results in the field.
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