The stochastic Weibull diffusion process: Computational aspects and simulation

A. Nafidi, M. Bahij, B. Achchab and R. Gutiérrez-Sanchez

Applied Mathematics and Computation, 2019, vol. 348, issue C, 575-587

Abstract: This paper presents a new stochastic diffusion process, in which the mean function is proportional to the density function of the Weibull distribution. This is considered a useful model for survival populations, reliability studies and life-testing experiments. The main features of the process are analysed, including the transition probability density function and conditional and non-conditional mean functions. The parameters of the process are estimated by maximum likelihood using discrete sampling. Newton-Raphson and simulated annealing numerical methods are proposed to solve the likelihood equations, and are compared using a simulation example.

Keywords: Stochastic Weibull model; Diffusion process estimation; Discrete sampling; Mean function; Newton–Raphson; Simulated annealing (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:348:y:2019:i:c:p:575-587

DOI: 10.1016/j.amc.2018.12.017

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