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

Provides an optimization method 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 algorithm is 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 when the number of samples is large and the number of mixture components is not too large. This implements the "mix-SQP" algorithm, with some improvements, described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2020) .


Reference manual

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install.packages("mixsqp")

0.3-54 by Peter Carbonetto, 3 years ago


https://github.com/stephenslab/mixsqp


Report a bug at https://github.com/stephenslab/mixsqp/issues


Browse source code at https://github.com/cran/mixsqp


Authors: Youngseok Kim [aut] , Peter Carbonetto [aut, cre] , Mihai Anitescu [aut] , Matthew Stephens [aut] , Jason Willwerscheid [ctb] , Jean Morrison [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports utils, stats, irlba, Rcpp

Suggests testthat, knitr, rmarkdown

Linking to Rcpp, RcppArmadillo


Imported by ashr, ebnm, susieR.


See at CRAN