Описание: Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods.
Автор: Pavel V. Shevchenko Название: Modelling Operational Risk Using Bayesian Inference ISBN: 3642423531 ISBN-13(EAN): 9783642423536 Издательство: Springer Рейтинг: Цена: 14635.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This has formally defined operational risk and introduced corresponding capital requirements. Many banks are undertaking quantitative modelling of operational risk using the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity of operational risk losses.
Автор: Hanns L. Harney Название: Bayesian Inference ISBN: 364205577X ISBN-13(EAN): 9783642055775 Издательство: Springer Рейтинг: Цена: 11581.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Solving a longstanding problem in the physical sciences, this text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. The text is written at introductory level, with many examples and exercises.
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: Marta Blangiardo,Michela Cameletti Название: Spatial and Spatio–temporal Bayesian Models with R – INLA ISBN: 1118326555 ISBN-13(EAN): 9781118326558 Издательство: Wiley Рейтинг: Цена: 9496.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics.
Описание: The Integrated Nested Laplace Approximation is a popular method for approximate Bayesian inference. INLA is an alternative to other methods for Bayesian inference, such as Markov Chain Monte Carlo, that are more computationally demanding. In addition, the R-INLA package for the R statistical software provides a way to fit such models in practice
Автор: Morgan Название: Counterfactuals and Causal Inference ISBN: 1107694167 ISBN-13(EAN): 9781107694163 Издательство: Cambridge Academ Рейтинг: Цена: 5702.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.
Описание: Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models.
Автор: Bailer-Jones Coryn A L Название: Practical Bayesian Inference ISBN: 1316642216 ISBN-13(EAN): 9781316642214 Издательство: Cambridge Academ Рейтинг: Цена: 6336.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume introduces the major concepts of probability and statistics and the computational tools students need to extract information from data in the presence of uncertainty. Using a simple and intuitive Bayesian approach, the emphasis throughout is on the principles and showing how these methods can be implemented in practice.
Автор: Edited by Kim-Anh Do Название: Bayesian Inference for Gene Expression and Proteomics ISBN: 052186092X ISBN-13(EAN): 9780521860925 Издательство: Cambridge Academ Рейтинг: Цена: 11405.00 р. Наличие на складе: Поставка под заказ.
Описание: The interdisciplinary nature of bioinformatics presents a research challenge in integrating concepts, methods, software and multiplatform data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high-throughput data, such as proteomic profiles that arise from mass spectrometry experiments. This book discusses the development and application of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as molecular and structural biology. The Bayesian approach has the advantage that evidence can be easily and flexibly incorporated into statistical methods. A basic overview of the biological and technical principles behind multi-platform high-throughput experimentation is followed by expert reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery and regulatory networks, and Bayesian networks and gene interactions.
Автор: Bailer-Jones Coryn A. L. Название: Practical Bayesian Inference: A Primer for Physical Scientists ISBN: 1107192110 ISBN-13(EAN): 9781107192119 Издательство: Cambridge Academ Рейтинг: Цена: 13622.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume introduces the major concepts of probability and statistics and the computational tools students need to extract information from data in the presence of uncertainty. Using a simple and intuitive Bayesian approach, the emphasis throughout is on the principles and showing how these methods can be implemented in practice.
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