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aksarkar/r-mixsqp

r-mixsqp

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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>.

Installation

To install this package, run one of the following:

Conda
$conda install aksarkar::r-mixsqp

Usage Tracking

0.3.45.dev1
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Downloads (Last 6 months): 0

About

Summary

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>.

Last Updated

Aug 15, 2020 at 16:23

License

MIT + file LICENSE

Total Downloads

44

Supported Platforms

linux-64

Home

https://github.com/stephenslab/mixsqp