Fitting Ornstein-Uhlenbeck-type Student's t-processes in Stan with applications for population dynamics data

Ornstein-Uhlenbeck (OU) processes are a mean reverting process and is used to model dynamics in biology, physics, and finance. I fit an extension of the OU process that is driven by a Lévy process with Student's t-marginals rather than Brownian motion with Gaussian marginals, which allows for heavy-tailed increments. I implement four formulations of the Student-t OU-type model in Stan and compare the sampling performance on both real and simulated population dynamic data.