Bayesian Inference in the Social Sciences (2014) by Ivan Jeliazkov & Xin-She Yang [Dr.Soc]seeders: 19
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Bayesian Inference in the Social Sciences (2014) by Ivan Jeliazkov & Xin-She Yang [Dr.Soc] (Size: 16.43 MB)
Description Bayesian Inference in the Social Sciences Author: Ivan Jeliazkov, Xin-She Yang Hardcover: 352 pages Publisher: Wiley; 1 edition (September 29, 2014) Language: English ISBN-10: 1118771214 ISBN-13: 978-1118771211 Format: PDF  Summary: Emphasizing interdisciplinary coverage, Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus. Bayesian Inference in the Social Sciences features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include: Real-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance State-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website Interdisciplinary coverage from well-known international scholars and practitioners [Amazon] Seed, Share, Gain knowledge || Don't forget to give thumbs up For any problem with my uploads or trouble with downloading, please PM me. Thanks. Sharing Widget |