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Bayesian optimization of hyperparameters from noisy marginal likelihood estimates

Gustafsson, Oskar; Villani, Mattias; Stockhammar, Pär - In: Journal of applied econometrics 38 (2023) 4, pp. 577-595

Persistent link: https://www.econbiz.de/10014288027

Bayesian Analysis of DSGE Models—Some Comments

Adolfson, Malin; Linde, Jesper; Villani, Mattias - In: Econometric Reviews 26 (2007) 2-4, pp. 173-185

Sungbae An and Frank Schorfheide have provided an excellent review of the main elements of Bayesian inference in Dynamic Stochastic General Equilibrium (DSGE) models. Bayesian methods have, for reasons clearly outlined in the paper, a very natural role to play in DSGE analysis, and the appeal of...

Persistent link: https://www.econbiz.de/10005511955

Modeling Conditional Densities Using Finite Smooth Mixtures

Li, Feng; Villani, Mattias; Kohn, Robert - Sveriges Riksbank - 2010

Smooth mixtures, i.e. mixture models with covariate-dependent mixing weights, are very useful flexible models for conditional densities. Previous work shows that using too simple mixture components for modeling heteroscedastic and/or heavy tailed data can give a poor fit, even with a large...

Persistent link: https://www.econbiz.de/10008671765

Dynamic mixture-of-experts models for longitudinal and discrete-time survival data

Quiroz, Matias; Villani, Mattias - Sveriges Riksbank - 2013

estimated using a Bayesian approach via a highly efficient Markov Chain Monte Carlo (MCMC) algorithm with tailored proposals and …

Persistent link: https://www.econbiz.de/10010818846

Generalized smooth finite mixtures

Villani, Mattias; Kohn, Robert; Nott, David J. - In: Journal of Econometrics 171 (2012) 2, pp. 121-133

model parameter being a deterministic function of covariates through a link function. Our MCMC methodology allows for …

Persistent link: https://www.econbiz.de/10010588323

Speeding up MCMC by efficient data subsampling

Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015

The computing time for Markov Chain Monte Carlo (MCMC) algorithms can be prohibitively large for datasets with many … applications. We propose a simple way to adaptively choose the sample size m during the MCMC to optimize sampling efficiency for a …

Persistent link: https://www.econbiz.de/10011442889

Scalable MCMC for large data problems using data subsampling and the difference estimator

Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015

We propose a generic Markov Chain Monte Carlo (MCMC) algorithm to speed up computations for datasets with many …(n) complexity of regular MCMC by operating over local data clusters instead of the full sample when computing the likelihood. The … bankruptcy for a large data set. We document a significant speed up in comparison to the standard MCMC on the full dataset. …

Persistent link: https://www.econbiz.de/10011442891

Speeding up MCMC by delayed acceptance and data subsampling

Quiroz, Matias; Villani, Mattias; Kohn, Robert - 2015

Persistent link: https://www.econbiz.de/10011442895

Evaluating an estimated new Keynesian small open economy model

Adolfson, Malin; Laséen, Stefan; Lindé, Jesper; … - 2007

This paper estimates and tests a new Keynesian small open economy model in the tradition of Christiano, Eichenbaum, and Evans (2005) and Smets and Wouters (2003) using Bayesian estimation techniques on Swedish data. To account for the switch to an inflation targeting regime in 1993 we allow for...

Persistent link: https://www.econbiz.de/10010320727

Flexible modeling of conditional distributions using smooth mixtures of asymmetric student T densities

Li, Feng; Villani, Mattias; Kohn, Robert - 2009

A general model is proposed for flexibly estimating the density of a continuous response variable conditional on a possibly high-dimensional set of covariates. The model is a finite mixture of asymmetric student-t densities with covariate dependent mixture weights. The four parameters of the...

Persistent link: https://www.econbiz.de/10010320729