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Bayesian Inference in the Social Sciences
Ivan Jeliazkov; Xin-She Yang
John Wiley & Sons Inc (2014)
Kovakantinen kirja
123,80
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Bayesian Model Comparison
Ivan Jeliazkov; Dale J. Poirier
Emerald Publishing Limited (2014)
Kovakantinen kirja
196,10
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling
Ivan Jeliazkov; Justin Tobias
Emerald Publishing Limited (2019)
Kovakantinen kirja
141,40
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling
Ivan Jeliazkov; Justin Tobias
Emerald Publishing Limited (2019)
Kovakantinen kirja
134,90
Tuotetta lisätty
ostoskoriin kpl
Siirry koriin
Bayesian Inference in the Social Sciences
123,80 €
John Wiley & Sons Inc
Sivumäärä: 352 sivua
Asu: Kovakantinen kirja
Julkaisuvuosi: 2014, 31.10.2014 (lisätietoa)
Kieli: Englanti
Presents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance

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


Bayesian Inference in the Social Sciences is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.

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Tilaustuote | Arvioimme, että tuote lähetetään meiltä noin 4-5 viikossa | Tilaa jouluksi viimeistään 27.11.2024
Myymäläsaatavuus
Helsinki
Tapiola
Turku
Tampere
Bayesian Inference in the Social Scienceszoom
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ISBN:
9781118771211
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