https://abraham1011.r-universe.devRecent package updates in abraham1011R-universehttps://github.com/abraham1011.pnghttps://abraham1011.r-universe.devFri, 10 Apr 2026 08:03:18 GMTpedroabraham.montoya@gmail.com (Pedro Abraham Montoya Calzada)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.https://github.com/r-universe/abraham1011/actions/runs/29001424332Fri, 10 Apr 2026 08:03:18 GMTmixediffusion1.0.1successhttps://abraham1011.r-universe.devhttps://github.com/cran/mixediffusionpedroabraham.montoya@gmail.com (Pedro Abraham Montoya Calzada)Provides tools for estimating the Remaining Useful Life (RUL) of degrading systems using linear mixed-effects models and creating a health index. It supports both univariate and multivariate degradation signals. For multivariate inputs, the signals are merged into a univariate health index prior to modeling. Linear and exponential degradation trajectories are supported (the latter using a log transformation). Remaining Useful Life (RUL) distributions are estimated using Bayesian updating for new units, enabling on-site predictive maintenance. Based on the methodology of Liu and Huang (2016) <doi:10.1109/TASE.2014.2349733>.https://github.com/r-universe/abraham1011/actions/runs/29638400285Fri, 05 Sep 2025 04:29:45 GMTdegradr1.0.1successhttps://abraham1011.r-universe.devhttps://github.com/abraham1011/degradr