title: Fitting dynamic growth models of biological phenomena from sample observations through Gaussian diffusion processes.
abstract: This paper addresses the building of stochastic models that adequately describe dynamic phenomena and, in particular, those that occur in the Biosciences. In this context, the empirical fitting of a Gaussian diffusion process from sample data of a dynamic growth phenomenon is considered. In order to do this, a methodology based on approximations to its mean and variance functions is presented. Finally, several applications based on simulated and real data have been carried out.
authors: Departamento de Estadística e Investigación Operativa, Universidad de Granada, Spain.
authors: Antonio J
authors: AJ
authors: Barrera-García
authors: Patricia
authors: P
authors: Román-Román
authors: Francisco
authors: F
authors: Torres-Ruiz
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D006128:Growth / Q000502:physiology*; D008954:Models, Biological; D016011:Normal Distribution; D011817:Rabbits; D013269:Stochastic Processes; D013997:Time Factors