A multivariate continuous (and discrete) time dynamic modelling package for panel and time series data, using linear stochastic differential equations. Contains a faster frequentist set of functions using OpenMx for single subject and mixed-effects (random intercepts only) structural equation models, or a hierarchical Bayesian implementation using Stan that allows for random effects over all model parameters. Allows for modelling of multiple noisy measurements of multiple stochastic processes, time varying input / event covariates, and time invariant covariates used to predict the parameters.
|Author||Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph]|
|Date of publication||2017-05-17 19:48:56 UTC|
|Maintainer||Charles Driver <email@example.com>|
|Package repository||View on CRAN|
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