ino: Initialization of Numerical Optimization

Implementation of initialization strategies for the numerical optimization of real-valued functions, in particular likelihood functions of statistical models.

Version: 0.2.0
Depends: R (≥ 4.0.0), optimizeR
Imports: ggplot2, rlang, mvtnorm, crayon, cli, progress, dplyr, foreach, doSNOW, ao (≥ 0.2.3)
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), purrr, pracma, fHMM
Published: 2022-09-29
Author: Lennart Oelschläger ORCID iD [aut, cre], Marius Ötting ORCID iD [aut]
Maintainer: Lennart Oelschläger <oelschlaeger.lennart at gmail.com>
BugReports: https://github.com/loelschlaeger/ino/issues
License: GPL (≥ 3)
URL: https://github.com/loelschlaeger/ino
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ino results

Documentation:

Reference manual: ino.pdf
Vignettes: Example: Hidden Markov Model
Example: Probit Model
Introduction

Downloads:

Package source: ino_0.2.0.tar.gz
Windows binaries: r-devel: ino_0.1.0.zip, r-release: ino_0.1.0.zip, r-oldrel: ino_0.2.0.zip
macOS binaries: r-release (arm64): ino_0.1.0.tgz, r-oldrel (arm64): ino_0.1.0.tgz, r-release (x86_64): ino_0.1.0.tgz, r-oldrel (x86_64): ino_0.1.0.tgz
Old sources: ino archive

Linking:

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