mixsqp
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) doi:10.1080/10618600.2019.1689985.
- Version0.3-54
- R versionunknown
- LicenseMIT
- Needs compilation?Yes
- mixsqp citation info
- Last release12/20/2023
Documentation
Team
Peter Carbonetto
Matthew Stephens
Show author detailsRolesAuthorJason Willwerscheid
Show author detailsRolesContributorJean Morrison
Show author detailsRolesContributorYoungseok Kim
Show author detailsRolesAuthorMihai Anitescu
Show author detailsRolesAuthor
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Last 30 days
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