Applied Probability
From Random Sequences to Stochastic Processes
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Beschreibung
This textbook addresses postgraduate students in applied mathematics, probability, and statistics, as well as computer scientists, biologists, physicists and economists, who are seeking a rigorous introduction to applied stochastic processes. Pursuing a pedagogic approach, the content follows a path of increasing complexity, from the simplest random sequences to the advanced stochastic processes. Illustrations are provided from many applied fields, together with connections to ergodic theory, information theory, reliability and insurance. The main content is also complemented by a wealth of examples and exercises with solutions.
This textbook addresses postgraduate students in applied mathematics, probability, and statistics, as well as computer scientists, biologists, physicists and economists, who are seeking a rigorous introduction to applied stochastic processes. Pursuing a pedagogic approach, the content follows a path of increasing complexity, from the simplest random sequences to the advanced stochastic processes. Illustrations are provided from many applied fields, together with connections to ergodic theory, information theory, reliability and insurance. The main content is also complemented by a wealth of examples and exercises with solutions.
Presents a comprehensive course on applied stochastic processes Includes a wealth of exercises with detailed solutions Provides numerous examples in reliability, information theory, production, risk, and other areas Builds a bridge between regular textbooks on probability theory and advanced monographs
Autor*in
Valérie Girardin
Themen in »Applied Probability«
Probability Random sequences Random processes Markov chains Semi-Markov processes Martingales Stochastic topology Central limit theorem Law of large numbers Statistical distributions Stopping time theorem Conditional expectation Stochastic processes
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“The primary audience of the book are students studying mathematics at a university and Ph.D. students in applied mathematics. It can also be served as a course at master’s and doctoral’s levels in applied probability. And finally, it is conceived as a support for the researchers and engineers dealing with stochastic modelling.” (Anatoliy Swishchuk, zbMATH 1434.60002, 2020)
“It is intended for students (at master or PhD level) in applied mathematics as well as researchers and engineers dealing with stochastic modeling issues. … Finally, the readers who want to get their hands on the different notions presented in the book will find at the end of each section a series of exercises with their solutions.” (Julien Poisat, Mathematical Reviews, October, 2019)
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