mixsqp: Sequential Quadratic Programming for Fast Maximum-Likelihood
Estimation of Mixture Proportions
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)
<doi:10.1080/10618600.2019.1689985>.
| Version: |
0.3-54 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
utils, stats, irlba, Rcpp (≥ 0.12.15) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat, knitr, rmarkdown |
| Published: |
2023-12-20 |
| DOI: |
10.32614/CRAN.package.mixsqp |
| Author: |
Youngseok Kim [aut],
Peter Carbonetto [aut, cre],
Mihai Anitescu [aut],
Matthew Stephens [aut],
Jason Willwerscheid [ctb],
Jean Morrison [ctb] |
| Maintainer: |
Peter Carbonetto <peter.carbonetto at gmail.com> |
| BugReports: |
https://github.com/stephenslab/mixsqp/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/stephenslab/mixsqp |
| NeedsCompilation: |
yes |
| Citation: |
mixsqp citation info |
| In views: |
Optimization |
| CRAN checks: |
mixsqp results |
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