Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions

Provides optimization algorithms based on sequential quadratic programming (SQP) for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithms are expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver (called by function "KWDual" in the 'REBayes' package), and they are expected to arrive at solutions more quickly in large data sets. The algorithms are described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2012) .


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0.1-79 by Peter Carbonetto, 2 months ago

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Authors: Youngseok Kim [aut] , Peter Carbonetto [aut, cre] , Mihai Anitescu [aut] , Matthew Stephens [aut]

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports stats, Rcpp

Suggests Rmosek, REBayes, testthat, knitr, rmarkdown

Linking to Rcpp, RcppArmadillo

System requirements: C++11

See at CRAN