Modeling and Applications to Random Processes
By (author) Gregory K. Miller
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Probability by Gregory K. Miller
Book DescriptionImprove Your Probability of Mastering This Topic This book takes an innovative approach to calculus-based probability theory, considering it within a framework for creating models of random phenomena. The author focuses on the synthesis of stochastic models concurrent with the development of distribution theory while also introducing the reader to basic statistical inference. In this way, the major stochastic processes are blended with coverage of probability laws, random variables, and distribution theory, equipping the reader to be a true problem solver and critical thinker. Deliberately conversational in tone, Probability is written for students in junior- or senior-level probability courses majoring in mathematics, statistics, computer science, or engineering. The book offers a lucid and mathematicallysound introduction to how probability is used to model random behavior in the natural world. The text contains the following chapters: Modeling Sets and Functions Probability Laws I: Building on the Axioms Probability Laws II: Results of Conditioning Random Variables and Stochastic Processes Discrete Random Variables and Applications in Stochastic Processes Continuous Random Variables and Applications in Stochastic Processes Covariance and Correlation Among Random Variables Included exercises cover a wealth of additional concepts, such as conditional independence, Simpson's paradox, acceptance sampling, geometric probability, simulation, exponential families of distributions, Jensen's inequality, and many non-standard probability distributions.
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Book DetailsISBN: 9780471458920
(242mm x 163mm x 29mm)
Imprint: John Wiley & Sons Inc
Publisher: John Wiley & Sons Inc
Publish Date: 19-Sep-2006
Country of Publication: United States
Books By Author Gregory K. Miller
Elements of Applied Stochastic Processes, Hardback (September 2002)» View all books by Gregory K. Miller
This third edition of the successful Elements of Applied Stochastic Processes improves on the last edition by condensing the material and organizing it into a more teachable format. With more in-depth coverage of Markov chains and simple Markov process, the authors provide added emphasis to statistical inference in stochastic processes.
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Author Biography - Gregory K. Miller
GREGORY K. MILLER, PHD, is Associate Professor of Statistics in the Department of Mathematics and Statistics at Stephen F. Austin State University in Nacogdoches, Texas. He is a coauthor, with U. Narayan Bhat, of Elements of Applied Stochastic Processes, Third Edition (Wiley).
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