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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 217.3 kB | win-64/r-mixsqp-0.3_17-r36h796a38f_0.tar.bz2  4 years and 11 months ago 1049 main cf202003
conda 215.7 kB | win-64/r-mixsqp-0.3_17-r35h796a38f_0.tar.bz2  4 years and 11 months ago 1069 main cf202003
conda 223.4 kB | osx-64/r-mixsqp-0.3_17-r35hc5da6b9_0.tar.bz2  4 years and 11 months ago 342 main cf202003
conda 224.8 kB | osx-64/r-mixsqp-0.3_17-r36hc5da6b9_0.tar.bz2  4 years and 11 months ago 338 main cf202003
conda 215.9 kB | linux-64/r-mixsqp-0.3_17-r36h0357c0b_0.tar.bz2  4 years and 11 months ago 3079 main cf202003
conda 214.8 kB | linux-64/r-mixsqp-0.3_17-r35h0357c0b_0.tar.bz2  4 years and 11 months ago 3117 main cf202003

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