Computational Features and Applications of Inference in the Stochastic of Inhomogeneous Gompertz Diffusion Process with Discrete Sampling

EasyChair Preprint 10496

Abstract

In this study, We consider the Gompertz diffusion process-based stochastic inhomogeneous model. We begin by obtaining the analytical formulation for the process's probabilistic properties, the mean functions (conditional and non-conditional). Then, using the maximum likelihood technique and discrete sampling, we estimate the model's parameters. Finally, we used the stochastic inhomogeneous Gompertz diffusion process to analyze the development of the electric power consumption in Morocco in order to assess this method's capacity for modeling actual data.

Keyphrases: Electric power consumption., Gompertz diffusion Model, statistical inference

@booklet{EasyChair:10496,
  author    = {Nadia Makhlouki and Ahmed Nafidi and Boujemaâ Achchab},
  title     = {Computational Features and Applications of Inference in the Stochastic of Inhomogeneous Gompertz Diffusion Process with Discrete Sampling},
  howpublished = {EasyChair Preprint 10496},
  year      = {EasyChair, 2023}}