Bayes Rules!: An Introduction to Applied Bayesian Modeling, Johnson Alicia A., Ott Miles Q., Dogucu Mine
Автор: Johnson Alicia A., Ott Miles Q., Dogucu Mine Название: Bayes Rules!: An Introduction to Applied Bayesian Modeling ISBN: 0367255391 ISBN-13(EAN): 9780367255398 Издательство: Taylor&Francis Рейтинг: Цена: 67360.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience. It empowers readers to weave Bayesian approaches into their everyday practice.
Автор: Gelman Название: Bayesian Data Analysis, Third Edition ISBN: 1439840954 ISBN-13(EAN): 9781439840955 Издательство: Taylor&Francis Рейтинг: Цена: 73920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.
Автор: Downey Allen Название: Think Bayes: Bayesian Statistics in Python ISBN: 149208946X ISBN-13(EAN): 9781492089469 Издательство: Wiley Рейтинг: Цена: 47510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: If you know how to program, you`re ready to tackle Bayesian statistics. With this book, you`ll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics.
Автор: Martin Osvaldo Название: Bayesian Analysis with Python - Second Edition: Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ ISBN: 1789341655 ISBN-13(EAN): 9781789341652 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Bayesian inference uses probability distributions and Bayes` theorem to build flexible models. The book uses PyMC3 to abstract all the mathematical and computational details from this process allowing readers to solve a wide range of problems in data science.
Автор: Heard Nick Название: An Introduction to Bayesian Inference, Methods and Computation ISBN: 3030828077 ISBN-13(EAN): 9783030828073 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models.
Автор: Fred J. Hickernell, Peter Kritzer Название: Multivariate Algorithms and Information-Based Complexity ISBN: 3110633116 ISBN-13(EAN): 9783110633115 Издательство: Walter de Gruyter Цена: 128870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The series is devoted to the publication of high-level monographs, surveys and proceedings which cover the whole spectrum of computational and applied mathematics.
The books of this series are addressed to both specialists and advanced students.
Interested authors may submit book proposals to the Managing Editor or to any member of the Editorial Board.
Managing Editor Ulrich Langer, RICAM, Linz, Austria; Johannes Kepler University Linz, Austria
Автор: Mengersen Kerrie L., Pudlo Pierre, Robert Christian P. Название: Case Studies in Applied Bayesian Data Science: Cirm Jean-Morlet Chair, Fall 2018 ISBN: 3030425525 ISBN-13(EAN): 9783030425524 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor.
Автор: V Stone Dr James Название: Bayes` Rule ISBN: 0993367917 ISBN-13(EAN): 9780993367915 Издательство: Неизвестно Рейтинг: Цена: 107290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The die is cast when the malefic King Ajutu realizes that he has been betrayed thrice over on Nkem`s account. With Nkem, Odera, and Namdi deeming they are no longer within easy striking distance of the king, the king charges his goons with the task of silencing them for good. When Nkem, Odera, and Namdi come to terms with what they`re up against, they form a frantic alliance with the king`s twin, Prince Ikuku, and unwittingly the estranged Queen Nena. As they also enlist the help of the Children of the Shadows, will King Ajutu, along with his gentry, become too hot to handle, or will he and his camarilla meet more than their match in the ever-growing alliance? In Children of the Shadows: Firmness of Purpose, the fight for justice and peace, and for the innocent child victims of the supposedly banned Mkpataku ritual reaches boiling point.
Автор: Francesco Archetti; Antonio Candelieri Название: Bayesian Optimization and Data Science ISBN: 3030244938 ISBN-13(EAN): 9783030244934 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume brings together the main results in the field of Bayesian Optimization (BO), focusing on the last ten years and showing how, on the basic framework, new methods have been specialized to solve emerging problems from machine learning, artificial intelligence, and system optimization. It also analyzes the software resources available for BO and a few selected application areas. Some areas for which new results are shown include constrained optimization, safe optimization, and applied mathematics, specifically BO's use in solving difficult nonlinear mixed integer problems. The book will help bring readers to a full understanding of the basic Bayesian Optimization framework and gain an appreciation of its potential for emerging application areas. It will be of particular interest to the data science, computer science, optimization, and engineering communities.
Автор: Weber Название: Benefits of Bayesian Network Models ISBN: 184821992X ISBN-13(EAN): 9781848219922 Издательство: Wiley Рейтинг: Цена: 146730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The application of Bayesian Networks (BN) or Dynamic Bayesian Networks (DBN) in dependability and risk analysis is a recent development. A large number of scientific publications show the interest in the applications of BN in this field. Unfortunately, this modeling formalism is not fully accepted in the industry.
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