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Limit Theorems in Probability, Statistics and Number Theory

Limit theorems and asymptotic results form a central topic in probability theory and mathematical statistics. New and non-classical limit;

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Limit Distributions for Sums of Independent Random Vectors

central limit theory of random vectors, which lies at the heart of probability and statistics. The authors develop the central limit theory;

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Approximation Theorems of Mathematical Statistics

methods of proof and techniques of application. The manipulation of probability theorems to obtain statistical theorems is emphasized.;

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Random Summation

, information properties of probability distributions, and asymptotic behavior of doubly stochastic Poisson processes. Random Summation: Limit Theorems;

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Random Summation

, information properties of probability distributions, and asymptotic behavior of doubly stochastic Poisson processes. Random Summation: Limit Theorems;

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Introduction to Probability and Statistics

probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit;

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Introduction to Probability and Statistics

probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit;

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Reproducing Kernel Hilbert Spaces in Probability and Statistics

more fruitful and promising applications, including statistical signal processing, nonparametric curve estimation, random measures, limit;

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Nonconventional Limit Theorems And Random Dynamics

theory but recently it turned out that main limit theorems of probability theory, such as central, local and Poisson limit theorems can also be;

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Probability and Measure Theory

topics in analysis. It provides extensive coverage of conditional probability and expectation, strong laws of large numbers, martingale theory;

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Probability The Classical Limit Theorems

probability, via random walks, Brownian motion, the law of large numbers and the central limit theorem, to aspects of ergodic theorems, equilibrium;

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Probability: The Classical Limit Theorems

probability, via random walks, Brownian motion, the law of large numbers and the central limit theorem, to aspects of ergodic theorems, equilibrium;

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Uniform Central Limit Theorems

second half introduces probability based on measure theory, including laws of large numbers, ergodic theorems, the central limit theorem;

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Limit Theorems of Probability Theory

A collection of research level surveys on certain topics in probability theory by a well-known group of researchers. The book will be;

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On the Estimation of Multiple Random Integrals and U-Statistics

This work starts with the study of those limit theorems in probability theory for which classical methods do not work. In many cases some;

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Probability Theory

This book is intended as an introduction to Probability Theory and Mathematical Statistics for students in mathematics, the physical;

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Studies in the Theory of Random Processes

limit theorems for Markov processes. Specialists, researchers, and students in the field of probability will find it a source of important;

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Probability, Statistics, and Stochastic Processes

three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes;

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Measure and Probability

This book covers the fundamentals of measure theory and probability theory. It begins with the construction of Lebesgue measure via;

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Measure and Probability

This book covers the fundamentals of measure theory and probability theory. It begins with the construction of Lebesgue measure via;

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Stochastic Geometry, Spatial Statistics and Random Fields: Asymptotic Methods

is focused on asymptotic methods in geometric probability including weak and strong limit theorems for random spatial structures (point processes;

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History of the Central Limit Theorem

. In this context the book also describes the historical development of analytical probability theory and its tools, such as characteristic;

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Probability

in probability: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and;

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Handbook of Probability

Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing;

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Probability

This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems;

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Random Matrices And Random Partitions

This book is aimed at graduate students and researchers who are interested in the probability limit theory of random matrices and random;

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Some Limit Theorems in Statistics

A discussion of some topics in the theory of large deviations such as moment-generating functions and Chernoff's theorem, and of aspects;

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