Modelling Operational Risk Using Bayesian Inference, Pavel V. Shevchenko
Автор: Constantin Zopounidis Название: New Operational Approaches for Financial Modelling ISBN: 3790810436 ISBN-13(EAN): 9783790810431 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume in the "Contributions to Management Science" series covers new operational approaches for financial modelling. Topics include: high-performance computing and finance; financial markets, portfolio theory and selection; financial forecasting; and corporate finance.
Автор: F. Mosteller; D. L. Wallace Название: Applied Bayesian and Classical Inference ISBN: 1461297591 ISBN-13(EAN): 9781461297598 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: We did several distinct full studies for the Federalist papers as well as many minor side studies. Although a chapter cannot compre- hensively Gover a field where many books now appear, it can mention most ofthe book-length works and the main thread of authorship` studies published in English.
Описание: Proceedings of the Frontis workshop on Bayesian Statistics and quality modelling in the agro-food production chain, held in Wageningen, The Netherlands, 1-14 May 2003
Описание: This book offers a comprehensive guide to the modelling of operational risk using possibility theory. The book offers a complete assessment of fuzzy methods for determining both value at risk (VaR) and subjective value at risk (SVaR), together with a stability estimation of VaR and SVaR.
Описание: This book offers a comprehensive guide to the modelling of operational risk using possibility theory. The book offers a complete assessment of fuzzy methods for determining both value at risk (VaR) and subjective value at risk (SVaR), together with a stability estimation of VaR and SVaR.
Автор: Harney Название: Bayesian Inference ISBN: 3319416421 ISBN-13(EAN): 9783319416427 Издательство: Springer Рейтинг: Цена: 13555.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition offers a comprehensive introduction to the analysis of data using Bayes rule. It generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. This is particularly useful when the observed parameter is barely above the background or the histogram of multiparametric data contains many empty bins, so that the determination of the validity of a theory cannot be based on the chi-squared-criterion. In addition to the solutions of practical problems, this approach provides an epistemic insight: the logic of quantum mechanics is obtained as the logic of unbiased inference from counting data. New sections feature factorizing parameters, commuting parameters, observables in quantum mechanics, the art of fitting with coherent and with incoherent alternatives and fitting with multinomial distribution. Additional problems and examples help deepen the knowledge. Requiring no knowledge of quantum mechanics, the book is written on introductory level, with many examples and exercises, for advanced undergraduate and graduate students in the physical sciences, planning to, or working in, fields such as medical physics, nuclear physics, quantum mechanics, and chaos.
Автор: Ghosal, Subhashis. Название: Fundamentals of Nonparametric Bayesian Inference ISBN: 0521878268 ISBN-13(EAN): 9780521878265 Издательство: Cambridge Academ Рейтинг: Цена: 12989.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.
Автор: Peter M?ller; Brani Vidakovic Название: Bayesian Inference in Wavelet-Based Models ISBN: 0387988858 ISBN-13(EAN): 9780387988856 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapters in Part II explore different approaches to prior modeling, using independent priors. Papers in the Part III discuss decision theoretic aspects of such prior models. In Part IV, some aspects of prior modeling using priors that account for dependence are explored.
Автор: Hanns L. Harney Название: Bayesian Inference ISBN: 364205577X ISBN-13(EAN): 9783642055775 Издательство: Springer Рейтинг: Цена: 13270.00 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.
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