Dynr is pronounced the same as “dinner.” The inspiration came from relating the procedures of fitting dynamic models to things done surrounding dinner, such as gathering ingredients (data), preparing recipes (code for different submodels), cooking (estimation) and serving (presentation of results).
Dynr can handle a broad class of linear and nonlinear discrete- and continuous-time models, with regime-switching properties in C, while maintaining intuitive specification functions in R.