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Creator: Geweke, John Series: Working paper (Federal Reserve Bank of Minneapolis. Research Department) Number: 532 Abstract:
This paper integrates and extends some recent computational advances in Bayesian inference with the objective of more fully realizing the Bayesian promise of coherent inference and model comparison in economics. It combines Markov chain Monte Carlo and independence Monte Carlo with importance sampling to provide an efficient and generic method for updating posterior distributions. It exploits the multiplicative decomposition of marginalized likelihood into predictive factors, to compute posterior odds ratios efficiently and with minimal further investment in software. It argues for the use of predictive odds ratios in model comparison in economics. Finally, it suggests procedures for public reporting that will enable remote clients to conveniently modify priors, form posterior expectations of their own functions of interest, and update the posterior distribution with new observations. A series of examples explores the practicality and efficiency of these methods.
This paper was prepared for the inaugural Colin Clark Lecture, Australasian Meetings of the Econometric Society, July 1994.
Palabra clave: Computation, Model comparison, Bayesian inference, and Econometric modeling Tema: C53 - Forecasting Models; Simulation Methods and C11 - Bayesian Analysis: General
Creator: Richard, Jean François and Zhang, Wei Series: Simulation-based inference in econometrics Descripción:
Original document was hand-written so not in OCR searchable format.
Palabra clave: Simulation, Econometric modeling, and Latent variables Tema: C15 - Econometric and statistical methods : General - Simulation methods and C32 - Multiple or simultaneous equation models - Time-series models ; Dynamic quantile regressions