The book develops the necessary background in probability theory underlying diverse treatments of stochastic processes and ...
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                This book aims at a middle ground between the introductory books on derivative securities and those that provide advanced ...
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                This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course ...
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                This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course ...
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                According to Leo Breiman (1968), probability theory has a right and a left hand. The right hand refers to rigorous mathematics, ...
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                In this revised and extended version of his course notes from a 1-year course at Scuola Normale Superiore, Pisa, the author ...
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                The present textbook contains the recordsof a two–semester course on que- ing theory, including an introduction to matrix–analytic ...
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                This book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures ...
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                This book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians ...
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                The book provides a comprehensive coverage of the main statistical analysis topics important for practical applications such ...
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                The main purpose of the book is to give a rigorous, yet mostly nontechnical, introduction to the most important and useful ...
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                Applied Stochastic Processes uses a distinctly applied framework to present the most important topics in the field of stochastic ...
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                Stochastic calculus and excursion theory are very efficient tools to obtain either exact or asymptotic results about Brownian ...
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                This introductory chapter discusses such notions as determinism, chaos and randomness, p- dictibility and unpredictibility, ...
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                This book presents elementary probability theory with interesting and well-chosen applications that illustrate the theory. ...
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                This Bayesian modeling book provides an operational methodology for conducting Bayesian inference, rather than focusing on ...
Lire la suiteThis book demonstrates how nonlinear/non-Gaussian Bayesian time series estimation methods were used to produce a probability ...
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                With its many easy-to-follow mathematical examples, this book takes the reader on an almost chronological trip through the ...
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                Classical Methods of Statistics is a blend of theory and practical statistical methods written for graduate students and ...
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                This book explores recent topics in quantitative finance with an emphasis on applications and calibration to time-series. ...
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