Efficient Maximum Likelihood Identification [R package EMLI version 0.1.0]

EMLI: Efficient Maximum Likelihood Identification

Provides implementations of computationally efficient maximum likelihood estimation algorithms for system identification tasks. Currently, one such algorithm is implemented which identifies the one-dimensional cumulative structural equation model with normality assumptions. The corresponding scientific paper is yet to be published, therefore the relevant reference is not available yet.

Version:	0.1.0
Imports:	stats
Published:	2022-05-17
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.pdf

Downloads:

Package source:	EMLI_0.1.0.tar.gz
Windows binaries:	r-devel: EMLI_0.1.0.zip, r-release: EMLI_0.1.0.zip, r-oldrel: EMLI_0.1.0.zip
macOS binaries:	r-release (arm64): EMLI_0.1.0.tgz, r-oldrel (arm64): EMLI_0.1.0.tgz, r-release (x86_64): EMLI_0.1.0.tgz, r-oldrel (x86_64): EMLI_0.1.0.tgz

Linking:

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