Estimators which have locally uniform expansions are shown in this paper to be asymptotically equivalent to M-estimators. The M-functionals corresponding to these M-estimators are seen to be locally uniformly Fréchet differentiable. Other conditions for M-functionals to be locally uniformly Fréchet differentiable are given. An example of a commonly used estimator which is robust against outliers is given to illustrate that the locally uniform expansion need not be valid
We examine challenges to estimation and inference when the objects of interest are nondifferentiable...
We study the problem of performing statistical inference based on robust estimates when the distrib...
The differentiability properties of statistical functionals have several interesting applications. W...
AbstractIt has been shown (Reeds, 1976, Ph.D. dissertation, Harvard University) that the remainder t...
AbstractA good robust functional should, if possible, be efficient at the model, smooth, and have a ...
This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating fu...
We present a uniformization of Reeken's macroscopic differentiability (see [5]), discuss its relatio...
AbstractLet (X1, Y1),…, (Xn, Yn) be i.i.d. rv's and let m(x) = E(Y|X = x) be the regression curve of...
This article develops a theory of maximum empirical likelihood estimation and empirical likelihood r...
We propose a method to conduct uniform inference for the (optimal) value function, that is, the func...
AbstractIn a variety of statistical problems one needs to manipulate a sequence of stochastic functi...
AbstractSuppose that U=(U1,…,Ud) has a Uniform([0,1]d) distribution, that Y=(Y1,…,Yd) has the distri...
Let (X1, Y1),..., (Xn, Yn) be i.i.d. rv's and let m(x) = E(YX = x) be the regression curve of Y on X...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
This paper explores the uniformity of inference for parameters of interest in nonlinear models with ...
We examine challenges to estimation and inference when the objects of interest are nondifferentiable...
We study the problem of performing statistical inference based on robust estimates when the distrib...
The differentiability properties of statistical functionals have several interesting applications. W...
AbstractIt has been shown (Reeds, 1976, Ph.D. dissertation, Harvard University) that the remainder t...
AbstractA good robust functional should, if possible, be efficient at the model, smooth, and have a ...
This paper deals with the Fisher-consistency, weak continuity and differentiability of estimating fu...
We present a uniformization of Reeken's macroscopic differentiability (see [5]), discuss its relatio...
AbstractLet (X1, Y1),…, (Xn, Yn) be i.i.d. rv's and let m(x) = E(Y|X = x) be the regression curve of...
This article develops a theory of maximum empirical likelihood estimation and empirical likelihood r...
We propose a method to conduct uniform inference for the (optimal) value function, that is, the func...
AbstractIn a variety of statistical problems one needs to manipulate a sequence of stochastic functi...
AbstractSuppose that U=(U1,…,Ud) has a Uniform([0,1]d) distribution, that Y=(Y1,…,Yd) has the distri...
Let (X1, Y1),..., (Xn, Yn) be i.i.d. rv's and let m(x) = E(YX = x) be the regression curve of Y on X...
This thesis has two distinct parts. The second and third chapters concern the theory and practical ...
This paper explores the uniformity of inference for parameters of interest in nonlinear models with ...
We examine challenges to estimation and inference when the objects of interest are nondifferentiable...
We study the problem of performing statistical inference based on robust estimates when the distrib...
The differentiability properties of statistical functionals have several interesting applications. W...