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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 (2012) <arXiv:1806.01412>.

Installation

To install this package, run one of the following:

Conda
$conda install conda-forge::r-mixsqp

Usage Tracking

0.3_54
0.3_48
0.3_43
0.3_17
0.2_2
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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

Nov 17, 2022 at 06:52

License

MIT

Total Downloads

637.6K

Version Downloads

258.6K

Supported Platforms

linux-aarch64
linux-64
macOS-64
linux-ppc64le
win-64

Unsupported Platforms

macOS-arm64 Last supported version: 0.3_54