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Bayesian methods in macroeconometrics
2008Macroeconometrics encompasses a large variety of probability models for macroeconomic time series as well as estimation and inference procedures to study the determinants of economic growth, to examine the sources of business cycle fluctuations, to understand the propagation of shocks, to generate forecasts, and to predict the effects of economic ...
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Bayesian methods in global optimization
Journal of Global Optimization, 1991The paper reviews methods which have been proposed for solving global optimization problems in the framework of the Bayesian paradigm. Three main approaches are singled out. In the first approach, called the Random Function Approach, methods are based on the idea of introducing a probabilistic model for the objective function in the form of a random ...
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2009
Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information ...
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Bayesian methods are rapidly becoming popular tools for making statistical inference in various fields of science including biology, engineering, finance, and genetics. One of the key aspects of Bayesian inferential method is its logical foundation that provides a coherent framework to utilize not only empirical but also scientific information ...
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2006
Abstract This chapter provides a brief introduction to the theory and computation of Bayesian statistics and its applications to molecular evolution. It uses simple examples, such as distance estimation under the JC69 model, to introduce the general principles.
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Abstract This chapter provides a brief introduction to the theory and computation of Bayesian statistics and its applications to molecular evolution. It uses simple examples, such as distance estimation under the JC69 model, to introduce the general principles.
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This comprehensive Handbook presents the current state of art in the theory and methodology of macroeconomic data analysis. It is intended as a reference for graduate students and researchers interested in exploring new methodologies, but can also be employed as a graduate text.
Mikkel Bennedsen, Allan H. Würtz
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Mikkel Bennedsen, Allan H. Würtz
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2002
BACKGROUND AND INTRODUCTION Introduction Motivation and Justification Why Are We Uncertain about Probability? Bayes' Law Conditional Inference with Bayes' Law Historical Comments The Scientific Process in Our Social Sciences Introducing Markov Chain Monte Carlo Techniques Exercises SPECIFYING BAYESIAN MODELS Purpose Likelihood Theory and Estimation The
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BACKGROUND AND INTRODUCTION Introduction Motivation and Justification Why Are We Uncertain about Probability? Bayes' Law Conditional Inference with Bayes' Law Historical Comments The Scientific Process in Our Social Sciences Introducing Markov Chain Monte Carlo Techniques Exercises SPECIFYING BAYESIAN MODELS Purpose Likelihood Theory and Estimation The
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Efficient Bayesian method for characterizing multiple soil parameters using parametric bootstrap
Computers and Geotechnics, 2023Dian-Qing Li
exaly
A bivariate Bayesian method for interval-valued regression models
Knowledge-Based Systems, 2022Min Xu, Zhongfeng Qin
exaly