Journal ArticleDOI
Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
TLDR
All of the methods in this work can fail to detect the sorts of convergence failure that they were designed to identify, so a combination of strategies aimed at evaluating and accelerating MCMC sampler convergence are recommended.Abstract:
A critical issue for users of Markov chain Monte Carlo (MCMC) methods in applications is how to determine when it is safe to stop sampling and use the samples to estimate characteristics of the distribution of interest. Research into methods of computing theoretical convergence bounds holds promise for the future but to date has yielded relatively little of practical use in applied work. Consequently, most MCMC users address the convergence problem by applying diagnostic tools to the output produced by running their samplers. After giving a brief overview of the area, we provide an expository review of 13 convergence diagnostics, describing the theoretical basis and practical implementation of each. We then compare their performance in two simple models and conclude that all of the methods can fail to detect the sorts of convergence failure that they were designed to identify. We thus recommend a combination of strategies aimed at evaluating and accelerating MCMC sampler convergence, including ap...read more
Citations
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Journal ArticleDOI
A Bayesian analysis of autoregressive models with random normal coefficients
Thelma Sáfadi,Pedro A. Morettin +1 more
TL;DR: In this paper, a Bayesian analysis for an autoregressive model with random normal coefficients (RCA) with conjugate priors and improper vague priors is presented.
Book
New Directions in Macromodelling
TL;DR: In this paper, the authors present a comparison of bivariate GARCH processes within the conditional ECM framework with the SVEqCM framework, and the optimal lag structure selection in VAR and VEC models.
Journal ArticleDOI
Investigating causal biological relationships between reproductive performance traits in high-performing gilts and sows1.
K Chitakasempornkul,Mariana B Meneget,Guilherme J. M. Rosa,Fernando B. Lopes,Abigail Jager,Márcio A D Gonçalves,Steve S Dritz,Michael D. Tokach,Robert D. Goodband,Nora M. Bello +9 more
TL;DR: The results suggest distinctly heterogeneous mechanistic networks of reproductive physiology for gilts and sows, consistent with physiological differences between the groups, which have potential practical implications for integrated understanding and differential management of giltsand sows to enhance efficiency of swine production systems.
Posted ContentDOI
Modelling Claims Run-Off with Reversible Jump Markov Chain Monte Carlo Methods
TL;DR: In this paper, the authors describe a new approach to modelling the development of claims run-off triangles, which replaces the usual ad hoc practical process of extrapolating a development pattern to obtain tail factors with an objective procedure.
Book ChapterDOI
The New Keynesian Approach to Dynamic General Equilibrium Modeling: Models, Methods and Macroeconomic Policy Evaluation
Sebastian Schmidt,Volker Wieland +1 more
TL;DR: In this article, the authors provide a hands-on approach to New Keynesian models and their uses for macroeconomic policy analysis by providing a framework for model comparison along with a database that includes a wide variety of macroeconomic models.
References
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Journal ArticleDOI
Robust Locally Weighted Regression and Smoothing Scatterplots
TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.