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mixsqp
View on CRAN: Click
here
Download and install mixsqp package within the R console
Install from CRAN:
install.packages("mixsqp")
Install from Github:
library("remotes")
install_github("cran/mixsqp") Install by package version:
library("remotes")
install_version("mixsqp", "0.3-54") Attach the package and use:
library("mixsqp")
Maintained by
Peter Carbonetto
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-14
Latest Update: 2023-12-20
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)
.
How to cite:
Peter Carbonetto (2018). mixsqp: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions. R package version 0.3-54, https://cran.r-project.org/web/packages/mixsqp. Accessed 16 Jul. 2026.
Previous versions and publish date:
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Other R packages that mixsqp depends,
imports, suggests or enhances
Complete documentation for mixsqp
Functions, R codes and Examples using
the mixsqp R package
Some associated functions: mixobjective . mixsqp-package . mixsqp . simulatemixdata . tacks .
Some associated R codes: RcppExports.R . datasim.R . misc.R . mixsqp-package.R . mixsqp.R . objective.R . tacks.R . tsvd.R . zzz.R . Full mixsqp package functions and examples
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