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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 (2018) <arXiv:1806.01412>.

Installation

To install this package, run one of the following:

Conda
$conda install r_test::r-mixsqp

Usage Tracking

0.2_2
0.1_97
2 / 8 versions selected
Total downloads: 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 (2018) <arXiv:1806.01412>.

Information Last Updated

Apr 22, 2025 at 15:32

License

MIT

Total Downloads

13

Platforms

Linux 64 Version: 0.1_97
macOS 64 Version: 0.2_2
Win 64 Version: 0.1_97