Probability Theory & Applications

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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...

CRC Standard Probability and Statistics Tables and Formulae, Student Edition

Stephen Kokoska
August 29, 2017

Users of statistics in their professional lives and statistics students will welcome this concise, easy-to-use reference for basic statistics and probability. It contains all of the standardized statistical tables and formulas typically needed plus material on basic statistics topics, such as...

Stochastic Processes: An Introduction, Second Edition

Peter Watts Jones
July 27, 2017

Based on a highly popular, well-established course taught by the authors, Stochastic Processes: An Introduction, Second Edition discusses the modeling and analysis of random experiments using the theory of probability. It focuses on the way in which the results or outcomes of experiments vary and...

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...

Reliability Models for Engineers and Scientists

Mark P. Kaminskiy
March 29, 2017

A discussion of the basic reliability concepts and models, Reliability Models for Engineers and Scientists demystifies modern mathematical reliability models. Requiring very little mathematical background on the reader’s part, this concise book introduces the models by focusing on their physical...

Change-Point Analysis in Nonstationary Stochastic Models

Boris Brodsky
March 23, 2017

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures...