Mathematics

Probability Theory & Applications

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Algorithmics of Nonuniformity: Tools and Paradigms

Micha Hofri, Hosam Mahmoud
July 17, 2018

Algorithmics of Nonuniformity is a solid presentation about the analysis of algorithms, and the data structures that support them. Traditionally, algorithmics have been approached either via a probabilistic view or an analytic approach. The authors adopt both approaches and bring them together...

Large Covariance and Autocovariance Matrices

Arup Bose, Monika Bhattacharjee
July 03, 2018

Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models. The prerequisites...

Patterned Random Matrices

Arup Bose
May 17, 2018

Large dimensional random matrices (LDRM) with specific patterns arise in econometrics, computer science, mathematics, physics, and statistics. This book provides an easy initiation to LDRM. Through a unified approach, we investigate the existence and properties of the limiting spectral distribution...

Mathematics of Keno and Lotteries

Mark Bollman
March 27, 2018

Mathematics of Keno and Lotteries is an elementary treatment of the mathematics, primarily probability and simple combinatorics, involved in lotteries and keno. Keno has a long history as a high-advantage, high-payoff casino game, and state lottery games such as Powerball are mathematically similar...

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference

Athanasios Christou Micheas
January 24, 2018

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks;...

Graph Searching Games and Probabilistic Methods

Anthony Bonato, Pawel Pralat
December 27, 2017

Graph Searching Games and Probabilistic Methods is the first book that focuses on the intersection of graph searching games and probabilistic methods. The book explores various applications of these powerful mathematical tools to games and processes such as Cops and Robbers, Zombie and Survivors,...

Bayesian Inference for Stochastic Processes

Lyle D. Broemeling
December 15, 2017

This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information). Initially, the book begins with a brief review of Bayesian inference and uses many examples...

Real Analysis and Probability

R. M. Dudley
December 08, 2017

Written by one of the best-known probabilists in the world this text offers a clear and modern presentation of modern probability theory and an exposition of the interplay between the properties of metric spaces and those of probability measures. This text is the first at this level to include...

Weakly Stationary Random Fields, Invariant Subspaces and Applications

Vidyadhar S. Mandrekar, David A. Redett
November 06, 2017

The first book to examine weakly stationary random fields and their connections with invariant subspaces (an area associated with functional analysis). It reviews current literature, presents central issues and most important results within the area. For advanced Ph.D. students,...

Stochastic Processes: An Introduction, Third Edition

Peter Watts Jones, Peter Smith
October 16, 2017

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments, where processes evolve over time. The text begins with a review of relevant fundamental probability...

Recursive Identification and Parameter Estimation

Han-Fu Chen, Wenxiao Zhao
October 12, 2017

Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying rigorous theoretical analysis, it presents the material and proposed algorithms in a manner that makes it easy to...

What Makes Variables Random: Probability for the Applied Researcher

Peter J. Veazie
May 03, 2017

What Makes Variables Random: Probability for the Applied Researcher provides an introduction to the foundations of probability that underlie the statistical analyses used in applied research. By explaining probability in terms of measure theory, it gives the applied researchers a conceptual...

Conferences

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