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A First Course in Probability and Markov Chains

in Probability and Markov Chains presents an introduction to the basic elements in probability and focuses on two main areas. The first part explores;

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Understanding Probability 3rd

Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies;

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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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Probability An Introduction 2Nd

' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains;

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Grinstead and Snell's Introduction to Probability

probability course taken by mathematics, the physical and social sciences, engineering, and computer science students. The text can be used in a;

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Finite Markov Chains and Algorithmic Applications

graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range;

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Non-Homogeneous Markov Chains and Systems

Features A broad and accessible overview of non-homogeneous Markov chains and systems Fills a significant gap in the current literature A;

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The Theory of Probability

This classic book is intended to be the first introduction to probability and statistics written with an emphasis on the analytic approach;

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Ergodic Behavior of Markov Processes

The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and;

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Finite Markov Processes and Their Applications

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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Markov Chains

knowledge of probability theory Covering both the theory underlying the Markov model and an array of Markov chain implementations, within a common;

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Applications of Markov Chains in Chemical Engineering

Markov chains make it possible to predict the future state of a system from its present state ignoring its past history. Surprisingly;

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Probability for Engineering, Mathematics, and Science, International Edition

, the text includes a self-contained chapter on finite Markov chains, which introduces the basic aspects of Markov chains and illustrates their;

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Probabilities of Counting Codes

how formulas can be found based on the rules of the probability theory, and their correctness is verified by a comparison with Markov chains.;

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Mathematics of Probability

independence and conditional expectations. The second half of the book deals with Gaussian random variables, with Markov chains, with a few continuous;

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Introduction to Hidden Semi-Markov Models

Markov chains and hidden Markov chains have applications in many areas of engineering and genomics. This book provides a basic introduction;

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Introduction to the Numerical Solution of Markov Chains

A cornerstone of applied probability, Markov chains can be used to help model how plants grow, chemicals react, and atoms diffuse--and;

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Markov Chains

with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing;

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Elements Of Stochastic Modelling

of probability theory and then covers the following topics: Markov chains, Markov decision processes, jump Markov processes, elements of queueing theory;

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Introduction To Probability Models

Introduction to Probability Models, Tenth Edition, provides an introduction to elementary probability theory and stochastic processes;

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Elementary Probability For Applications

combinatorial probability and Markov chains. Concise and focused, it is designed for a one-semester introductory course in probability for students who;

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Probability

An introduction to probability at the undergraduate level Chance and randomness are encountered on a daily basis. Authored by a highly;

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Probability with STEM Applications

basic properties of probability, random variables and their probability distributions, a brief introduction to statistical inference, Markov;

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Applied Probability Models with Optimization Applications

in the area of decision processes. After reviewing some basic notions of probability theory and stochastic processes, the author presents a;

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Probability, Markov Chains, Queues, and Simulation

Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that;

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