Package: iterLap
Type: Package
Title: Approximate probability densities by iterated Laplace
Approximations
Version: 1.1-2
Depends: quadprog, randtoolbox, parallel, R (>= 2.15)
Date: 2012-05-22
Author: Bjoern Bornkamp
Maintainer: Bjoern Bornkamp <bbnkmp@gmail.com>
Description: 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.
License: GPL
LazyLoad: yes
Packaged: 2012-05-22 20:05:33 UTC; bjoern
Repository: CRAN
Date/Publication: 2012-05-22 20:52:08

Title: Approximate Probability Densities by Iterated Laplace

Title: Print Loop Iterations at Exponentially Disparate Intervals
person("Steve", "Condylios", , "steve.condylios@gmail.com", c("aut", "cre",
Description: Know which loop iteration the code execution is up to by including
a single, convenient function call inside the loop.

Description: Support for iterators, which allow a programmer to
traverse through all the elements of a vector, list, or other

Title: Provides Iterator Construct for R
Description: Support for iterators, which allow a programmer to traverse
through all the elements of a vector, list, or other collection

through all the elements of a vector, list, or other collection of data.

Packaged: 2022-01-16 18:19:31 UTC; folashade

Title: Efficient iterator for permutations and combinations
Author: Randy Lai [aut, cre], Martin Broadhurst [aut]
Description: This package helps in 1) generating permutations and combinations with or without replacement; 2) with distinct items or non-distinct items (multiset); 3) calculating number of combinations or permutations in various situations. All generated sequences are in lexicographical order (AKA, dictionary order). The algorithms to generate permutations and combinations are memory efficient, only previous sequence is required to generate next sequence. These iteratively algorithms enable users to process all sequences without putting all results in the memory at the same time.  The algorithms are written in C/C++ and hence very computational efficient.