T-Growth Stochastic Model: Simulation and Inference via Metaheuristic Algorithms

The main objective of this work is to introduce a stochastic model associated with the one described by T-growth curve, which in turn modification logistic curve. By conveniently reformulating T it may be obtained as solution linear differential equation. This greatly simplifies mathematical treatment and allows diffusion process defined, derived from non-homogeneous lognormal process, whose mean function phenomenon under study viewed dynamic way. In these pages, distribution obtained, are its characteristics. maximum likelihood estimation procedure carried out optimization via metaheuristic algorithms. Thanks an exhaustive strategy bound parametric space, requirement for application various swarm-based A simulation presented show validity bounding example based on real data provided.