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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 2 months ago 1119 main cf202003
conda 205.0 kB | win-64/r-mixsqp-0.2_2-r35h796a38f_0.tar.bz2  5 years and 2 months ago 1129 main cf202003
conda 211.3 kB | osx-64/r-mixsqp-0.2_2-r35hc5da6b9_0.tar.bz2  5 years and 2 months ago 333 main cf202003
conda 212.7 kB | osx-64/r-mixsqp-0.2_2-r36hc5da6b9_0.tar.bz2  5 years and 2 months ago 330 main cf202003
conda 203.9 kB | linux-64/r-mixsqp-0.2_2-r36h0357c0b_0.tar.bz2  5 years and 2 months ago 3435 main cf202003
conda 202.9 kB | linux-64/r-mixsqp-0.2_2-r35h0357c0b_0.tar.bz2  5 years and 2 months ago 3416 main cf202003

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