Recent Advances in Semiparametric Bayesian Function Estimation

Fahrmeir, Ludwig (1998): Recent Advances in Semiparametric Bayesian Function Estimation. Collaborative Research Center 386, Discussion Paper 137

Abstract

Common nonparametric curve fitting methods such as spline smoothing, local polynomial regression and basis function approaches are now well developed and widely applied. More recently, Bayesian function estimation has become a useful supplementary or alternative tool for practical data analysis, mainly due to breakthroughs in computerintensive inference via Markov chain Monte Carlo simulation. This paper surveys recent developments in semiparametric Bayesian inference for generalized regression and outlines some directions in current research.

• Item Type: Paper (Research Paper)
• Faculties: Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386; Special Research Fields > Special Research Field 386
• Subjects: 500 Science > 510 Mathematics
• Language: English