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This text presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. This edition provides a completely rewritten and expanded part on probability theory. Along with additional examples,
Table des matières
PROBABILITY THEORY: RANDOM EVENTS AND THEIR PROBABILITIES. ONE-DIMENSIONAL RANDOM VARIABLES. MULTIDIMENSIONAL RANDOM VARIABLES. FUNCTIONS OF RANDOM VARIABLES. INEQUALITIES AND LIMIT THEOREMS.
STOCHASTIC PROCESSES: BASICS OF STOCHASTIC PROCESSES. RANDOM POINT PROCESSES. DISCRETE-TIME MARKOV CHAINS. CONTINUOUS-TIME MARKOV CHAINS. MARTINGALES. BROWNIAN MOTION. SPECTRAL ANALYSIS OF STATIONARY PROCESSES. REFERENCES. INDEX.
A propos de l'auteur
Frank Beichelt is an honorary professor in the School of Statistics and Actuarial Science at the University of Witwatersrand. His research focuses on probability theory and mathematical statistics, including stochastic modeling in reliability, maintenance, and safety analysis. He is the author/coauthor of numerous papers and books, including the Chapman & Hall/CRC book
Reliability and Maintenance: Networks and Systems. He holds a Dr. rer. nat. in mathematics and a Dr. sc. in engineering.
Résumé
This text presents a self-contained introduction to elementary probability theory and stochastic processes with a special emphasis on their applications in science, engineering, finance, computer science, and operations research. This edition provides a completely rewritten and expanded part on probability theory. Along with additional examples,
