resde: Estimation in Reducible Stochastic Differential Equations

Maximum likelihood estimation for univariate reducible stochastic differential equation models. Discrete, possibly noisy observations, not necessarily evenly spaced in time. Can fit multiple individuals/units with global and local parameters, by fixed-effects or mixed-effects methods. Ref.: Garcia, O. (2019) "Estimating reducible stochastic differential equations by conversion to a least-squares problem", Computational Statistics 34(1): 23-46, <doi:10.1007/s00180-018-0837-4>.

Version:	1.1
Imports:	stats, Deriv, nlme, methods
Suggests:	knitr
Published:	2023-05-19
DOI:	10.32614/CRAN.package.resde
Author:	Oscar Garcia [aut, cre]
Maintainer:	Oscar Garcia <garcia at dasometrics.net>
BugReports:	https://github.com/ogarciav/resde/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://github.com/ogarciav/resde/
NeedsCompilation:	no
Citation:	resde citation info
Materials:	NEWS
In views:	DifferentialEquations, TimeSeries
CRAN checks:	resde results

Documentation:

Reference manual:	resde.pdf
Vignettes:	Fitting Reducible SDE Models

Downloads:

Package source:	resde_1.1.tar.gz
Windows binaries:	r-devel: resde_1.1.zip, r-release: resde_1.1.zip, r-oldrel: resde_1.1.zip
macOS binaries:	r-release (arm64): resde_1.1.tgz, r-oldrel (arm64): resde_1.1.tgz, r-release (x86_64): resde_1.1.tgz, r-oldrel (x86_64): resde_1.1.tgz

Linking:

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