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An Introduction to Stochastic Processes with Applications to Biology

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes;

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Markov Processes and Applications

include: * The Monte Carlo method, discrete time Markov chains, the Poisson process and continuous time jump Markov processes.* An introduction to;

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An Introduction to Continuous-Time Stochastic Processes

Additional exercises Smoluchowski approximation of Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Edition will be;

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Controlled Markov Processes and Viscosity Solutions

This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It;

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Controlled Markov Processes and Viscosity Solutions

This book is an introduction to optimal stochastic control for continuous time Markov processes and the theory of viscosity solutions. It;

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Controlled Markov Processes and Viscosity Solutions

This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity;

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Levy Processes And Infinitely Divisible Distributions

introduction to stochastic processes in general. No specialist knowledge is assumed and proofs are given in detail. Systematic study is made of stable;

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Levy Processes and Infinitely Divisible Distributions

introduction to stochastic processes in general. No specialist knowledge is assumed and proofs are given in detail. Systematic study is made of stable;

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Stochastic Modeling and Analysis of Telecom Networks

of stochastic recursions from an ergodic theoretical perspective is also provided, as well as spatial point processes. Using these basic tools;

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Stochastic Processes An Introduction, Third Edition Chapman HallCRC Texts in Statistical Science

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition;

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Markov Processes from K. Ito's Perspective (AM-155)

introduction to continuous-time, stochastic processes.;

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Mathematical Statistics and Stochastic Processes

book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This;

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An Introduction to Stochastic Processes

A vigorous response to the challenges of incorporating computer use into the teaching and learning of stochastic processes, this book takes;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

begins with an introduction to relative optimization, including a comparison with the traditional approach of dynamic programming. The text then;

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

begins with an introduction to relative optimization, including a comparison with the traditional approach of dynamic programming. The text then;

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Stochastic Processes

Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition;

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Advanced Topics in Control and Estimation of State-Multiplicative Noisy Systems

appreciation of the text: a basic introduction to stochastic control processes, aspects of linear matrix inequality optimization, and MATLAB codes for;

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Brownian Motion and Stochastic Calculus

stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example;

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Stochastic Processes

Based on a highly popular, well-established course taught by the authors, Stochastic Processes: An Introduction, Second Edition discusses;

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Mathematical Finance

Taking continuous-time stochastic processes allowing for jumps as its starting and focal point, this book provides an accessible;

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Introduction to Stochastic Processes in

This book provides an accessible introduction to stochastic processes in physics and describes the basic mathematical tools of the trade;

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Bayesian Inference for Stochastic Processes

state space and continuous time and continuous state space. The elements necessary to understanding stochastic processes are then introduced;

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Bayesian Inference for Stochastic Processes

state space and continuous time and continuous state space. The elements necessary to understanding stochastic processes are then introduced;

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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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Stochastic Processes

This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way;

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Introduction to Stochastic Analysis

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide;

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Introduction to Option Pricing Theory

Since the appearance of seminal works by R. Merton, and F. Black and M. Scholes, stochastic processes have assumed an increasingly;

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