EMLI: Computationally Efficient Maximum Likelihood Identification of Linear Dynamical Systems

Provides implementations of computationally efficient maximum likelihood parameter estimation algorithms for models representing linear dynamical systems. Currently, two such algorithms (one offline and one online) are implemented for the single-output cumulative structural equation model with an additive-noise output measurement equation and assumptions of normality and independence. The corresponding scientific papers are referenced in the descriptions of the functions implementing these algorithms.

Version:	0.3.0
Imports:	stats
Published:	2025-09-17
DOI:	10.32614/CRAN.package.EMLI
Author:	Vytautas Dulskis [cre, aut], Leonidas Sakalauskas [aut]
Maintainer:	Vytautas Dulskis <vytautas.dulskis at gmail.com>
License:	GPL-2
Copyright:	Vilnius University Institute of Data Science and Digital Technologies
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	EMLI results

Documentation:

Reference manual:

EMLI.html , EMLI.pdf

Downloads:

Package source:	EMLI_0.3.0.tar.gz
Windows binaries:	r-devel: EMLI_0.2.0.zip, r-release: EMLI_0.2.0.zip, r-oldrel: EMLI_0.2.0.zip
macOS binaries:	r-release (arm64): EMLI_0.2.0.tgz, r-oldrel (arm64): EMLI_0.2.0.tgz, r-release (x86_64): EMLI_0.3.0.tgz, r-oldrel (x86_64): EMLI_0.2.0.tgz
Old sources:	EMLI archive

Linking:

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