We model a regression density nonparametrically so that at each value of the covariates the density is a mixture of … Experts ; Predictive inference ; Splines ; Value-at-Risk ; Variable selection …

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 …

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 …

Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the … uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function …