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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 GarciaORCID iD [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.html ,resde.pdf
Vignettes:Fitting Reducible SDE Models (source,R code)

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:

Please use the canonical formhttps://CRAN.R-project.org/package=resdeto link to this page.


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