title: A diffusion process to model generalized von Bertalanffy growth patterns: fitting to real data.
abstract: The von Bertalanffy growth curve has been commonly used for modeling animal growth (particularly fish). Both deterministic and stochastic models exist in association with this curve, the latter allowing for the inclusion of fluctuations or disturbances that might exist in the system under consideration which are not always quantifiable or may even be unknown. This curve is mainly used for modeling the length variable whereas a generalized version, including a new parameter b > or = 1, allows for modeling both length and weight for some animal species in both isometric (b = 3) and allometric (b not = 3) situations. In this paper a stochastic model related to the generalized von Bertalanffy growth curve is proposed. This model allows to investigate the time evolution of growth variables associated both with individual behaviors and mean population behavior. Also, with the purpose of fitting the above-mentioned model to real data and so be able to forecast and analyze particular characteristics, we study the maximum likelihood estimation of the parameters of the model. In addition, and regarding the numerical problems posed by solving the likelihood equations, a strategy is developed for obtaining initial solutions for the usual numerical procedures. Such strategy is validated by means of simulated examples. Finally, an application to real data of mean weight of swordfish is presented.
authors.affiliation: Departamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Granada. Avda. Fuentenueva s/n 18071 Granada, Spain. proman@ugr.es
authors.forename: Patricia
authors.initials: P
authors.lastname: Román-Román
authors.forename: Desirée
authors.initials: D
authors.lastname: Romero
authors.forename: Francisco
authors.initials: F
authors.lastname: Torres-Ruiz
mesh_terms: D000465:Algorithms; D000818:Animals; D048708:Cell Growth Processes; D003198:Computer Simulation; D004058:Diffusion; D006801:Humans; D016013:Likelihood Functions; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D011336:Probability; D013269:Stochastic Processes; D013997:Time Factors