Asymptotic properties of approximate maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with random effects

2018 ◽  
Vol 48 (8) ◽  
pp. 1890-1901
Author(s):  
Tian Xia ◽  
Xuejun Jiang ◽  
Xueren Wang
Keyword(s):  
Random Effects ◽  
Nonlinear Models ◽  
Asymptotic Properties ◽  
Likelihood Estimator

scholarly journals Maximum likelihood Estimation for Stochastic Differential Equations with two Random Effects in the Diffusion Coefficient

2016 ◽  
Vol 11 (10) ◽  
pp. 5697-5704
Author(s):  
Mohammed Sari Alsukaini ◽  
Alkreemawi khazaal Walaa ◽  
Wang Xiang Jun
Keyword(s):  
Differential Equation ◽  
Maximum Likelihood ◽  
Random Effects ◽  
Diffusion Coefficients ◽  
Likelihood Function ◽  
Asymptotic Properties ◽  
Likelihood Estimation ◽  
Likelihood Estimator ◽  
Unknown Parameters ◽  
Consistency And Asymptotic Normality

We study n independent stochastic processes(xi (t),tiЄ[o,t1 ],i=1,......n) defined by a stochastic differential equation with diffusion coefficients depending nonlinearly on a random variables  and  (the random effects).The distributions of the random effects Ñ„i,and,μi and  depends on unknown parameters which are to be estimated from the continuous observations of the processes xi (t) . When the distributions of the random effects Ñ„ ,μ, are Gaussian and exponential respectively, we obtained an explicit formula for the likelihood function and the asymptotic properties (consistency and asymptotic normality) of the maximum likelihood estimator (MLE) are derived when  tend to infinity.

scholarly journals SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES

2015 ◽  
Vol 32 (5) ◽  
pp. 1140-1177 ◽  
Author(s):  
Enno Mammen ◽  
Christoph Rothe ◽  
Melanie Schienle
Keyword(s):  
Nonlinear Models ◽  
Asymptotic Variance ◽  
Asymptotic Properties ◽  
Control Variable ◽  
Semiparametric Estimation ◽  
Nuisance Parameters ◽  
Infinite Dimensional ◽  
Asymptotically Normal ◽  
Endogenous Covariates ◽  
Nonstandard Problem

We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g., estimate nonlinear models with endogenous covariates when identification is achieved using control variable techniques. We study the asymptotic properties of estimators in this class, which is a nonstandard problem due to the presence of generated covariates. We give conditions under which estimators are root-nconsistent and asymptotically normal, derive a general formula for the asymptotic variance, and show how to establish validity of the bootstrap.

INFLUENCE ANALYSIS ON EXPONENTIAL NONLINEAR MODELS WITH RANDOM EFFECTS

2003 ◽  
Vol 23 (3) ◽  
pp. 297-308 ◽  
Author(s):  
Xuping Zhong ◽  
Jun Zhao ◽  
Haibin Wang ◽  
Bocheng Wei
Keyword(s):  
Random Effects ◽  
Nonlinear Models ◽  
Influence Analysis
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