mixsqp: 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) <arXiv:1806.01412>.

Package details

AuthorYoungseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb]
MaintainerPeter Carbonetto <[email protected]>
LicenseMIT + file LICENSE
Version0.1-97
URL https://github.com/stephenslab/mixsqp
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mixsqp")

Try the mixsqp package in your browser

Any scripts or data that you put into this service are public.

mixsqp documentation built on May 2, 2019, 6:34 a.m.