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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>.

copied from cf-staging / r-mixsqp
Type Size Name Uploaded Downloads Labels
conda 206.2 kB | win-64/r-mixsqp-0.2_2-r36h796a38f_0.tar.bz2  5 years and 16 days ago 1112 main cf202003
conda 205.0 kB | win-64/r-mixsqp-0.2_2-r35h796a38f_0.tar.bz2  5 years and 16 days ago 1121 main cf202003
conda 211.3 kB | osx-64/r-mixsqp-0.2_2-r35hc5da6b9_0.tar.bz2  5 years and 16 days ago 333 main cf202003
conda 212.7 kB | osx-64/r-mixsqp-0.2_2-r36hc5da6b9_0.tar.bz2  5 years and 16 days ago 329 main cf202003
conda 203.9 kB | linux-64/r-mixsqp-0.2_2-r36h0357c0b_0.tar.bz2  5 years and 16 days ago 3256 main cf202003
conda 202.9 kB | linux-64/r-mixsqp-0.2_2-r35h0357c0b_0.tar.bz2  5 years and 16 days ago 3238 main cf202003

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