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Markov Processes, Gaussian Processes, and Local Times

Written by two foremost researchers in the field, this book studies the local times of Markov processes by employing isomorphism theorems;

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Markov Processes, Gaussian Processes, and Local Times

This book was first published in 2006. Written by two of the foremost researchers in the field, this book studies the local times of Markov;

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Asymptotic Properties of Permanental Sequences

sequences related to birth and death processes and autoregressive Gaussian sequences using techniques from the theory of Gaussian processes and;

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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Stochastic Analysis for Gaussian Random Processes and Fields

Stochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic;

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Theory and Statistical Applications of Stochastic Processes

processes, martingales, Markov properties, continuity and related properties of trajectories with contemporary subjects: integration with respect to;

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Applied Stochastic Processes

This book uses a distinctly applied framework to present the most important topics in stochastic processes, including Gaussian and;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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Probability And Stochastic Processes

for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables;

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Hidden Markov Processes

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems;

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Statistical Inference for Piecewise-deterministic Markov Processes

, neuroscience, networks, finance... Such processes are defined by a deterministic motion punctuated by random jumps at random times, and offer simple;

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Markov Renewal and Piecewise Deterministic Processes

This book is aimed at researchers, graduate students and engineers who would like to be initiated to Piecewise Deterministic Markov;

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Competitive Markov Decision Processes

This book is intended as a text covering the central concepts and techniques of Competitive Markov Decision Processes. It is an attempt to;

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Competitive Markov Decision Processes

This book is intended as a text covering the central concepts and techniques of Competitive Markov Decision Processes. It is an attempt to;

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Visual Analysis of Behaviour

, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov;

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Inequalities In Analysis And Probability (Third Edition)

and diffusions, to Markov and point processes, renewal, branching and shock processes.In this third edition, the inequalities for martingales;

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First Look At Stochastic Processes, A

times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as;

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First Look At Stochastic Processes, A

times, branching processes, stock option pricing, and Markov Chain Monte Carlo (MCMC) algorithms.The focus is always on making the theory as;

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Markov Processes

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic;

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Stable Non-Gaussian Random Processes

This book presents similarity between Gaussian and non-Gaussian stable multivariate distributions and introduces the one-dimensional stable;

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Probability

in business and engineering, Markov chains investigations and approximations, Berstein-Hoeffding-type exponential inequalities useful for proving;

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Semi-Dirichlet Forms and Markov Processes

This book deals with analytic treatments of Markov processes. Symmetric Dirichlet forms and their associated Markov processes are important;

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Markov Processes and Applications

, Professor at Universite de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally;

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Stochastic Processes

Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks;

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Understanding Markov Chains

This book provides an undergraduate-level introduction to discrete and continuous-time Markov chains and their applications, with a;

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High Dimensional Probability III

The title High Dimensional Probability is used to describe the many tributaries of research on Gaussian processes and probability in Banach;

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Stochastic Analysis & Applications

Increments of a Class of Gaussian Processes; Random Walk Tests & Pseudorandom Number Generators; Increments Theory on Gaussian Processes; The Law;

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