iterLap (1.1-1)
Approximate probability densities by iterated Laplace Approximations.
http://cran.r-project.org/web/packages/iterLap
The iterLap (iterated Laplace approximation) algorithm approximates a general (possibly non-normalized) probability density on R^p, by repeated Laplace approximations to the difference between current approximation and true density (on log scale). The final approximation is a mixture of multivariate normal distributions and might be used for example as a proposal distribution for importance sampling (eg in Bayesian applications). The algorithm can be seen as a computational generalization of the Laplace approximation suitable for skew or multimodal densities.
Maintainer:
Bjoern Bornkamp
Author(s): Bjoern Bornkamp
License: GPL
Uses: quadprog, randtoolbox
Released over 1 year ago.
