Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

We develop a Bayesian method for nonparametric model—based quantile regression. The approach involves flexible Dirichlet process mixture models for the joint distribution of the response and the ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 49, No. 3 (September/septembre 2021), pp. 698-730 (33 pages) We propose a flexible Bayesian semiparametric quantile ...

In this paper we propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

2024 DEC 11 (NewsRx) -- By a News Reporter-Staff News Editor at Economics Daily Report -- Data detailed on Investment have been presented. According to news reporting out of Cleveland, Ohio, by NewsRx ...