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depscope/conda/r-mixsqp

r-mixsqp

condav0.3_48

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>.

License MITpermissive6 versions1 maintainers0 deps2,266 weekly dl
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Health breakdown0 – 100
10/25
maintenance
6/20
popularity
25/25
security
12/15
maturity
2/15
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First published · 2020-11-04 07:54:28.329000+00:00

Last updated · 2025-09-14 16:54:22.331000+00:00

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