Abstract
Evolutionary inferences from phylogenetic trees can be modeled stochastically using a range of mathematical frameworks. Among these, stochastic differential equations (SDEs) provide a particularly flexible and powerful approach to capturing the continuous-time dynamics of evolutionary processes. This review summarizes advances in stochastic modeling for trait evolution along a phylogenetic tree, with a focus on stochastic differential equations (SDEs), Gaussian and non-Gaussian processes, and time series models that can be expressed as special cases of general stochastic frameworks, depending on the questions being addressed or the types of data analyzed. We explore current developments and future research directions of stochastic modeling for phylogenetic comparative analysis in trait evolution.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call