A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation

In this paper, we introduce a new family of stochastic Lundqvist-Korf diffusion process, defined from a g-power of the Lundqvist-Korf diffusion process. First, we determine the probabilistic characteristics of the process, such as its analytic expression, the transition probability density function...

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Main Authors: Abdenbi El Azri, Ahmed Nafidi
Format: Article
Language:English
Published: Sciendo 2022-09-01
Series:Moroccan Journal of Pure and Applied Analysis
Subjects:
Online Access:https://doi.org/10.2478/mjpaa-2022-0025
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author Abdenbi El Azri
Ahmed Nafidi
author_facet Abdenbi El Azri
Ahmed Nafidi
author_sort Abdenbi El Azri
collection DOAJ
description In this paper, we introduce a new family of stochastic Lundqvist-Korf diffusion process, defined from a g-power of the Lundqvist-Korf diffusion process. First, we determine the probabilistic characteristics of the process, such as its analytic expression, the transition probability density function from the corresponding It ˆo stochastic differential equation and obtain the conditional and non-conditional mean functions. We then study the statistical inference in this process. The parameters of this process are estimated by using the maximum likelihood estimation method with discrete sampling, thus we obtain a nonlinear equation, which is achieved via the simulated annealing algorithm. Finally, the results of the paper are applied to simulated data.
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spelling doaj.art-5348ea92612248e8b1ba57b327ffa1a72022-12-22T04:16:41ZengSciendoMoroccan Journal of Pure and Applied Analysis2351-82272022-09-018336437410.2478/mjpaa-2022-0025A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulationAbdenbi El Azri0Ahmed Nafidi1University Hassan 1st of Settat, National School of Applied Sciences, Department of Mathematics and Computer Science, Laboratory of Systems Modelization and Analysis for Decision Support, B.P. 218, 26103, Berrechid, Morocco.University Hassan 1st of Settat, National School of Applied Sciences, Department of Mathematics and Computer Science, Laboratory of Systems Modelization and Analysis for Decision Support, B.P. 218, 26103, Berrechid, Morocco.In this paper, we introduce a new family of stochastic Lundqvist-Korf diffusion process, defined from a g-power of the Lundqvist-Korf diffusion process. First, we determine the probabilistic characteristics of the process, such as its analytic expression, the transition probability density function from the corresponding It ˆo stochastic differential equation and obtain the conditional and non-conditional mean functions. We then study the statistical inference in this process. The parameters of this process are estimated by using the maximum likelihood estimation method with discrete sampling, thus we obtain a nonlinear equation, which is achieved via the simulated annealing algorithm. Finally, the results of the paper are applied to simulated data.https://doi.org/10.2478/mjpaa-2022-0025stochastic lundqvist-korf diffusion processmaximum likelihood estimationsimulated annealing methodstatistical inference in diffusion processsimulation62m8662m2060h3060h3565c30
spellingShingle Abdenbi El Azri
Ahmed Nafidi
A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
Moroccan Journal of Pure and Applied Analysis
stochastic lundqvist-korf diffusion process
maximum likelihood estimation
simulated annealing method
statistical inference in diffusion process
simulation
62m86
62m20
60h30
60h35
65c30
title A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
title_full A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
title_fullStr A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
title_full_unstemmed A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
title_short A γ-power stochastic Lundqvist-Korf diffusion process: Computational aspects and simulation
title_sort γ power stochastic lundqvist korf diffusion process computational aspects and simulation
topic stochastic lundqvist-korf diffusion process
maximum likelihood estimation
simulated annealing method
statistical inference in diffusion process
simulation
62m86
62m20
60h30
60h35
65c30
url https://doi.org/10.2478/mjpaa-2022-0025
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