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Parametric inference for stochastic differential equations with random effects in the drift coefficient
Author(s) -
Alsukaini Mohammed Sari,
Xiangjun Wang
Publication year - 2016
Publication title -
international journal of advanced mathematical sciences
Language(s) - English
Resource type - Journals
ISSN - 2307-454X
DOI - 10.14419/ijams.v4i2.6328
Subject(s) - mathematics , estimator , stochastic differential equation , asymptotic distribution , parametric statistics , consistency (knowledge bases) , random variable , gaussian , random effects model , statistics , mathematical analysis , physics , medicine , meta analysis , quantum mechanics , geometry
In this paper we focus on estimating the parameters in the stochastic differential equations (SDE’s) with drift coefficients depending linearly on a random variables  and  .The distributions of the random effects  and  are depends on unknown parameters from the continuous observations of the independent processes . When  is an unknown parameter or restrict positive constant also studied in this paper. We propose the Gaussian distribution for the random effect  and the exponential distribution for the random effect    , we obtained an explicit formulas for the likelihood functions in each case and find the maximum likelihood estimators of the unknown parameters in the random effects and for the unknown parameter    . Consistency and asymptotic normality are studied just when  is normal random effect and  is constant.

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