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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 |
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 |
Reference manual: | resde.pdf |
Vignettes: |
Fitting Reducible SDE Models |
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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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