Flexible modeling of conditional distributions using smooth mixtures of asymmetric Student \(t\) densities

DOI10.1016/J.JSPI.2010.04.031zbMath1233.62076OpenAlexW3124028581MaRDI QIDQ993802

J. Martínez

Publication date: 20 September 2010

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.04.031

zbMATH Keywords

Markov chain Monte Carlomixture of expertsBayesian inferencevariable selectionvolatility modeling

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Bayesian inference (62F15) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (7)

POSTERIOR CONSISTENCY IN CONDITIONAL DENSITY ESTIMATION BY COVARIATE DEPENDENT MIXTURES ⋮ Semiparametric finite mixture of regression models with Bayesian P-splines ⋮ ADAPTIVE BAYESIAN ESTIMATION OF CONDITIONAL DENSITIES ⋮ Time-varying combinations of predictive densities using nonlinear filtering ⋮ Compliance Mixture Modelling with a Zero‐Effect Complier Class and Missing Data ⋮ Generalized smooth finite mixtures ⋮ A generalized class of skew distributions and associated robust quantile regression models

Uses Software

• SemiPar

Cites Work

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• Smoothly mixing regressions
• Density estimation through convex combinations of densities: Approximation and estimation bounds
• Interpretation and inference in mixture models: simple MCMC works
• Hierarchical mixtures-of-experts for exponential family regression models: Approximation and maximum likelihood estimation
• Bayesian analysis of mixture models with an unknown number of components\,--\,an alternative to reversible jump methods.
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Finite mixture and Markov switching models.
• Regression density estimation using smooth adaptive Gaussian mixtures
• Adaptive sampling for Bayesian variable selection
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Autoregressive Conditional Density Estimation
• Semiparametric Regression
• Bayesian mixture of splines for spatially adaptive nonparametric regression
• Computational and Inferential Difficulties with Mixture Posterior Distributions
• Bayesian Inference in Econometric Models Using Monte Carlo Integration
• Bayesian Density Estimation and Inference Using Mixtures
• Bayes Factors

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