{ "_id": "6a3b63f75cdecea1d681cc4e", "Encoding": "UTF-8", "Type": "Package", "Package": "mixsqp", "Version": "0.3-54", "Date": "2023-12-20", "Title": "Sequential Quadratic Programming for Fast Maximum-Likelihood\nEstimation of Mixture Proportions", "Authors@R": "c(person(\"Youngseok\",\"Kim\",role=\"aut\",\nemail=\"youngseok@uchicago.edu\"),\nperson(\"Peter\",\"Carbonetto\",role=c(\"aut\",\"cre\"),\nemail=\"peter.carbonetto@gmail.com\"),\nperson(\"Mihai\",\"Anitescu\",role=\"aut\"),\nperson(\"Matthew\",\"Stephens\",role=\"aut\"),\nperson(\"Jason\",\"Willwerscheid\",role=\"ctb\"),\nperson(\"Jean\",\"Morrison\",role=\"ctb\"))", "URL": "https://github.com/stephenslab/mixsqp", "BugReports": "https://github.com/stephenslab/mixsqp/issues", "Description": "Provides an optimization method based on sequential\nquadratic programming (SQP) for maximum likelihood estimation\nof the mixture proportions in a finite mixture model where the\ncomponent densities are known. The algorithm is expected to\nobtain solutions that are at least as accurate as the\nstate-of-the-art MOSEK interior-point solver (called by\nfunction \"KWDual\" in the 'REBayes' package), and they are\nexpected to arrive at solutions more quickly when the number of\nsamples is large and the number of mixture components is not\ntoo large. This implements the \"mix-SQP\" algorithm, with some\nimprovements, described in Y. Kim, P. Carbonetto, M. Stephens &\nM. 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