Publication Date:
Author(s): Lu Ou, Michael D. Hunter, Sy-Miin Chow
Publisher: R Foundation for Statistical Computing
Publication Type: Academic Journal Article
Journal Title: R Journal
Volume: 11
Issue: 1

Intensive longitudinal data in the behavioral sciences are often noisy, multivariate in nature, and may involve multiple units undergoing regime switches by showing discontinuities interspersed with continuous dynamics. Despite increasing interest in using linear and nonlinear differential/difference equation models with regime switches, there has been a scarcity of software packages that are fast and freely accessible. We have created an R package called dynr that can handle a broad class of linear and nonlinear discrete-and continuous-time models, with regime-switching properties and linear Gaussian measurement functions, in C, while maintaining simple and easy-tolearn model specification functions in R. We present the mathematical and computational bases used by the dynr R package, and present two illustrative examples to demonstrate the unique features of dynr.