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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
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 (2018) <arXiv:1806.01412>.

Last Updated

Dec 13, 2019 at 20:37

License

MIT

Total Downloads

13

Supported Platforms

macOS-64

Unsupported Platforms

linux-64 Last supported version: 0.1_97
win-64 Last supported version: 0.1_97