mixsqp-package

<p>Provides optimization algorithms 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. To learn more, visit
<a href="https://github.com/stephenslab/mixsqp">https://github.com/stephenslab/mixsqp</a>, and see the help for
function <code>mixsqp</code>.</p>

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>.

Peter Carbonetto

mixsqp

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

Youngseok Kim

Mihai Anitescu

Matthew Stephens

Jason Willwerscheid

Jean Morrison

mixsqp-package function

<p>Provides optimization algorithms 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. To learn more, visit
<a href='https://github.com/stephenslab/mixsqp'>https://github.com/stephenslab/mixsqp</a>, and see the help for
function <code>mixsqp</code>.</p>

mixsqp: Sequential Quadratic Programming for Fast Maximum-Likelihood
Estimation of Mixture Proportions — mixsqp-package

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

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

Description

Arguments