Encoding: UTF-8 Type: Package Package: mixsqp Version: 0.3-54 Date: 2023-12-20 Title: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions Authors@R: c(person("Youngseok","Kim",role="aut", email="youngseok@uchicago.edu"), person("Peter","Carbonetto",role=c("aut","cre"), email="peter.carbonetto@gmail.com"), person("Mihai","Anitescu",role="aut"), person("Matthew","Stephens",role="aut"), person("Jason","Willwerscheid",role="ctb"), person("Jean","Morrison",role="ctb")) URL: https://github.com/stephenslab/mixsqp BugReports: https://github.com/stephenslab/mixsqp/issues Depends: R (>= 3.3.0) Description: 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 not too large. This implements the "mix-SQP" algorithm, with some improvements, described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2020) . License: MIT + file LICENSE Imports: utils, stats, irlba, Rcpp (>= 0.12.15) Suggests: testthat, knitr, rmarkdown LinkingTo: Rcpp, RcppArmadillo LazyData: true NeedsCompilation: yes VignetteBuilder: knitr RoxygenNote: 7.1.2 Repository: https://stephenslab.r-universe.dev Date/Publication: 2023-12-20 17:47:41 UTC RemoteUrl: https://github.com/stephenslab/mixsqp RemoteRef: HEAD RemoteSha: 5146a57b2e2ae8a1ba2254bd8724998b87a92772 Packaged: 2026-06-24 04:53:14 UTC; root Author: Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb] Maintainer: Peter Carbonetto