iterLap: Approximate Probability Densities by Iterated Laplace Approximations
Version 1.1-3

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.

Package details

AuthorBjoern Bornkamp
Date of publication2017-08-05 19:28:28 UTC
MaintainerBjoern Bornkamp <[email protected]>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the iterLap package in your browser

Any scripts or data that you put into this service are public.

iterLap documentation built on Aug. 6, 2017, 1:03 a.m.