marqLevAlg - A Parallelized General-Purpose Optimization Based on Marquardt-Levenberg Algorithm
This algorithm provides a numerical solution to the problem of unconstrained local minimization (or maximization). It is particularly suited for complex problems and more efficient than the Gauss-Newton-like algorithm when starting from points very far from the final minimum (or maximum). Each iteration is parallelized and convergence relies on a stringent stopping criterion based on the first and second derivatives. See Philipps et al, 2021 <doi:10.32614/RJ-2021-089>.
Last updated
7.18 score 7 stars 17 dependents 11 scripts 7.7k downloadsJLPM - Joint Latent Process Models
Estimation of extended joint models with shared random effects. Longitudinal data are handled in latent process models for continuous (Gaussian or curvilinear) and ordinal outcomes while proportional hazard models are used for the survival part. We propose a frequentist approach using maximum likelihood estimation. See Saulnier et al, 2022 <doi:10.1016/j.ymeth.2022.03.003>.
Last updated
fortran
4.28 score 1 stars 1 scripts 351 downloadsweightQuant - Weights for Incomplete Longitudinal Data and Quantile Regression
Estimation of observation-specific weights for incomplete longitudinal data and bootstrap procedure for weighted quantile regressions. See Jacqmin-Gadda, Rouanet, Mba, Philipps, Dartigues (2020) for details <doi:10.1177/0962280220909986>.
Last updated
2.70 score 1 stars 3 scripts 763 downloads