Bayesian nonparametric mixture models represent a powerful statistical framework that extends traditional mixture modelling by allowing the number of mixture components to be inferred from the data ...

Bayesian hierarchical methods implemented for small area estimation focus on reducing the noise variation in published government official statistics by borrowing information among dependent response ...

Journal of Agricultural, Biological, and Environmental Statistics, Vol. 22, No. 4 (December 2017), pp. 585-601 (17 pages) We present a Bayesian nonparametric modeling approach to inference and risk ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...