A bayesian nonparametric density estimator
Peter Lenk · Journal of nonparametric statistics · 1993
Bayesian nonparametric density estimators required the construction of prior distributions on spaces of density functions. These prior distributions have parameters that control the amount of smoothness of the density estimator. Hierarchical Bayes methods provide a complete analysis of the density function and the smoothing parameters. This paper presents a posterior analysis of the unknown density by implementing a Markov chain Monte Carlo method.