Package: mixediffusion 1.0.1

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.

Authors:Pedro Abraham Montoya Calzada [aut, cre, cph], Rogelio Salinas Gutiérrez [aut, cph], Silvia Rodríguez-Narciso [aut, cph], Netzahualcóyotl Castañeda-Leyva [aut, cph]