Let τ be a prior distribution over the parameter space Θ for a given parametric model P θ, θ ∈ Θ. For the sample space X (over which P θ 's are probability measures) belonging to a general class of ...

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 ...

Several new tests are proposed for examining the adequacy of a family of parametric models against large nonparametric alternatives. These tests formally check if the bias vector of residuals from ...

Using the computer to design objects by modeling their components with real-world behaviors and attributes. Typically specialized for either mechanical design or building design, a parametric modeler ...