mixediffusion: Mixed-Effects Diffusion Models with General Drift

Provides tools for likelihood-based inference in one-dimensional stochastic differential equations with mixed effects using expectation–maximization (EM) algorithms. The package supports Wiener and Ornstein–Uhlenbeck diffusion processes with user-specified drift functions, allowing flexible parametric forms including polynomial, exponential, and trigonometric structures. Estimation is performed via Markov chain Monte Carlo EM.

Version:	1.0.0
Depends:	R (≥ 4.5)
Imports:	dplyr, adaptMCMC
Suggests:	testthat (≥ 3.0.0)
Published:	2026-03-20
DOI:	10.32614/CRAN.package.mixediffusion
Author:	Pedro Abraham Montoya Calzada [aut, cre, cph], Rogelio Salinas Gutiérrez [aut, cph], Silvia Rodríguez-Narciso [aut, cph], Netzahualcóyotl Castañeda-Leyva [aut, cph]
Maintainer:	Pedro Abraham Montoya Calzada <pedroabraham.montoya at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	mixediffusion results

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