We illustrate with examples when and how maximum likelihood estimators continue to be asymptotically efficient even under misspecified models. Also, we provide a necessary and sufficient condition under which a subset of the vector of MLE's retains its asymptotic efficiency under misspecified models even though the MLE itself is not fully asymptotic efficient
In completely specified models, where explicit formulae are derivable for the probabilities of obser...
In this paper we study the first-order efficiency and asymptotic normality of the maximum likelihood...
We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model...
It is well known that the maximum-likelihood estimator (MLE) under a misspecified model converges to...
Paper FRA-F6International audienceWe consider an hidden Markov model (HMM) with multidimensional obs...
Paper FRA-F6International audienceWe consider an hidden Markov model (HMM) with multidimensional obs...
This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Marko...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
International audienceThis article concerns maximum-likelihood estimation for discrete time homogene...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
We describe Monte Carlo approximation to the maximum likelihood estimator in models with intractabl...
In completely specified models, where explicit formulae are derivable for the probabilities of obser...
In completely specified models, where explicit formulae are derivable for the probabilities of obser...
In this paper we study the first-order efficiency and asymptotic normality of the maximum likelihood...
We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model...
It is well known that the maximum-likelihood estimator (MLE) under a misspecified model converges to...
Paper FRA-F6International audienceWe consider an hidden Markov model (HMM) with multidimensional obs...
Paper FRA-F6International audienceWe consider an hidden Markov model (HMM) with multidimensional obs...
This paper considers maximum likelihood (ML) estimation in a large class of models with hidden Marko...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
International audienceThis article concerns maximum-likelihood estimation for discrete time homogene...
The statistical properties of the maximum likelihood estimator (M.L.E.) of the parameters of a linea...
We describe Monte Carlo approximation to the maximum likelihood estimator in models with intractabl...
In completely specified models, where explicit formulae are derivable for the probabilities of obser...
In completely specified models, where explicit formulae are derivable for the probabilities of obser...
In this paper we study the first-order efficiency and asymptotic normality of the maximum likelihood...
We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model...