Package: iterLap 1.1-4

iterLap: Approximate Probability Densities by Iterated Laplace Approximations

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.

Authors:Bjoern Bornkamp

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5 exports 0.09 score 3 dependencies 5 scripts 323 downloads

Last updated 12 months agofrom:4d6444ffae. Checks:OK: 9. Indexed: yes.

Exports:GRApproxIMHISiterLapresample

Dependencies:quadprograndtoolboxrngWELL