mixsqp (0.3-17)

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Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions.

https://github.com/stephenslab/mixsqp
http://cran.r-project.org/web/packages/mixsqp

Provides an optimization method 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 algorithm is 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 when the number of samples is large and the number of mixture components is small. This implements the "mix-SQP" algorithm (without the low-rank approximation) described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2018) .

Maintainer: Peter Carbonetto
Author(s): Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb]

License: MIT + file LICENSE

Uses: irlba, Rcpp, testthat, rmosek, knitr, REBayes, rmarkdown

Released 23 days ago.


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