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Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures

Villani, Mattias; Kohn, Robert; Giordani, Paolo - Sveriges Riksbank - 2007

We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of …

Persistent link: https://www.econbiz.de/10005649083

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

Modeling conditional densities using finite smooth mixtures

Li, Feng; Villani, Mattias; Kohn, Robert - 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/10010320786

Bayesian bandwidth selection for a nonparametric regression model with mixed types of regressors

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - In: Econometrics : open access journal 4 (2016) 2, pp. 1-27

This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous … of the unobserved errors, while the regression function is estimated using the Nadaraya-Watson estimator admitting … nonparametric regression model of the Australian All Ordinaries returns and the kernel density estimation of gross domestic product …

Persistent link: https://www.econbiz.de/10011506243

Do maternal health problems influence child's worrying status? : evidence from British cohort study

Dai, Xianhua; Härdle, Wolfgang; Yu, Keming - 2014

prior distributions such as a normal distribution or a Laplace distribituion for regression coefficients, which may be … suitable for median regression and exhibit no robustness to outliers. This paper develops a quantile regression on linear panel …

Persistent link: https://www.econbiz.de/10010253468

Generalized smooth finite mixtures

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

We propose a general class of models and a unified Bayesian inference methodology for flexibly estimating the density of a response variable conditional on a possibly high-dimensional set of covariates. Our model is a finite mixture of component models with covariate-dependent mixing weights....

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

Modeling Conditional Densities Using Finite Smooth Mixtures

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

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

Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities

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

Persistent link: https://www.econbiz.de/10008469620

Bayesian semi-parametric realized conditional autoregressive expectile models for tail risk forecasting

Gerlach, Richard; Wang, Chao - In: Journal of financial econometrics 20 (2022) 1, pp. 105-138

Persistent link: https://www.econbiz.de/10012878188

Partially Censored Posterior for robust and efficient risk evaluation

Borowska, Agnieszka; Hoogerheide, Lennart; Koopman, Siem Jan - 2019

A novel approach to inference for a speciﬁc region of the predictive distribution is introduced. An important domain of application is accurate prediction of ﬁnancial risk measures, where the area of interest is the left tail of the predictive density of logreturns. Our proposed approach...

Persistent link: https://www.econbiz.de/10012214294