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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>.

Type Size Name Uploaded Downloads Labels
conda 200.2 kB | linux-64/r-mixsqp-0.3.45.dev1-r35hf484d3e_0.tar.bz2  4 years and 4 months ago 13 main
conda 239.0 kB | linux-64/r-mixsqp-0.3.43-r36h29659fb_0.tar.bz2  4 years and 7 months ago 5 main
conda 242.1 kB | linux-64/r-mixsqp-0.3.43-r35h29659fb_0.tar.bz2  4 years and 7 months ago 2 main
conda 210.3 kB | linux-64/r-mixsqp-0.3.17-r351h29659fb_0.tar.bz2  4 years and 11 months ago 4 main
conda 199.0 kB | linux-64/r-mixsqp-0.2.2-r351h29659fb_0.tar.bz2  5 years and 2 months ago 3 main
conda 171.4 kB | linux-64/r-mixsqp-0.1_97-r351h29659fb_0.tar.bz2  5 years and 9 months ago 5 main

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