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In the case where ρ is convex we give a set of sufficient conditions for the strong consistency of M-estimate of multiple regression coefficients.
Let (X, Y) be a pair of random variables such that X ranges over [0, 1] and Y is real-valued and let go(X) be the conditional expectation of Y given X. Based on a training sample, the piecewise polyno...
摘要 Consider the linear regression model Y_i=x_i′β+σ_ie_i,i=1,…,n,…, where E(e_i)=0, E(e_ie_j)=δ_(ij), 00. This paper shows that (i) if σ_i~2,i=1,2…, are known, then the necessary and sufficient condit...
Under a locally generalized Gaussian error's structure, we obtain strong uniform consistency for nonparametric regression function estimators and strong consistency for parametric component estimators...
In this paper, we propose several diagnostic measures for assessing the influence of an individual case and small perturbations on the transformation power estimator and the variance function estimato...
This paper deals with M-estimators for a semiparametric regression model Y=X^tβ_0 + g_0(T) + e,where Y is real-valued, T ranges over a nondegenerate compact interval, X ∈R^d, e is a random error, β_0 ...
In this paper, authors consider Bahadur asymptotic efficiency of MLE {\bar β}_{ML} of β, which is an unknown parameter vector in the semiparametric regression model Y_i=X_i~T β + g(T_i) + i, where g i...
The necessary and sufficient conditions for a linear estimator of a linear estimable function of regression coefficients in a general fixed effects linear model with the assumptions of normality to be...
For the general fixed effects linear model: Y=Xτ+ε,ε~N(0,V)(or N(0,σ~2V)), V≥0, we obtain the necessary and sufficient condition for LY+α to be admissible for Sτ in the class of all estimators under m...
In many situations, we are interested in selection of important variables whichare adequate for prediction under a linear regression model. In this paper, a fast selection procedure is proposed and is...
In this paper we study the estimation of the regression function. We establish a law ofthe iterated logarithm for the random window-width kernel estimator and, as an application, for a nearest neighbo...
Research on jump regression functions has not been adequate yet According to the information about the number of jumps, their positions and jump magnitudes, jump regression functions can be classified...

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