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