Approximate probability densities by iterated Laplace Approximations CRAN Task View: Bayesian (http://CRAN.R-project.org/view=Bayesian) 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. Software Depends: quadprog, randtoolbox, parallel, R (>= 2.15) Bjoern Bornkamp <bbnkmp@gmail.com> Bjoern Bornkamp GPL 2012-05-22 application/tgz http://CRAN.R-project.org/package=iterLap