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mixsqp

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

v0.3-54 · Dec 20, 2023 · MIT + file LICENSE

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) <DOI:10.1080/10618600.2019.1689985>.

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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (3)

imports

Dependency Network

Dependencies Reverse dependencies irlba Rcpp ashr ebnm susieR mixsqp

Version History

new 0.3-54 Mar 10, 2026
updated 0.3-54 ← 0.3-48 diff Dec 19, 2023
updated 0.3-48 ← 0.3-43 diff Nov 15, 2022
updated 0.3-43 ← 0.3-17 diff May 13, 2020
updated 0.3-17 ← 0.2-2 diff Jan 28, 2020
updated 0.2-2 ← 0.1-97 diff Oct 15, 2019
updated 0.1-97 ← 0.1-79 diff Feb 17, 2019
new 0.1-79 Nov 13, 2018