Sequential Monte Carlo (SMC) methods represent a classical set of techniques to simulate sequence probability measures through simple selection/mutation mechanism. However, the associated selection functions and mutation kernels usually depend on tuning parameters that are first importance for efficiency algorithm. A standard way address this problem is apply adaptive sequential (ASMC) methods,...

This article introduces the R package hermiter which facilitates estimation of univariate and bivariate probability density functions cumulative distribution along with full quantile (univariate) nonparametric correlation coefficients (bivariate) using Hermite series based estimators. The algorithms implemented in are particularly useful sequential setting (both stationary non-stationary) one-p...