iterLap (1.1-2)

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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 almost 5 years ago.


3 previous versions

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