Asymptotic normality of conditional distribution estimation in the single index model

Conditional density estimation in a censored single-index regression model

Asymptotic Distribution of the Hermite Normality Test

This paper presents some asymptotical results of the Hermite Normality test previously introduced. We show that the Hermite statistic S H is distributed under the null hypothesis as a quadratic form of normal variates and under the nonnull hypothesis as normal. The special case of tests with two polynomials is studied in details. Finally, we give some considerations for the choice of a best Her...

New estimation and inference procedures for a single-index conditional distribution model

In this article, a more flexible single-index regression model is employed to characterize the conditional distribution. The pseudo least integrated squares approach is proposed to estimate the index coefficients. As shown in the numerical results, our estimator outperforms the existing ones in terms of the mean squared error. Moreover, we provide the generalized cross-validation criteria for b...

Asymptotic Normality in Density Support Estimation

Estimation Gérard BIAU a,∗, Benôıt CADRE b, David M. MASON c and Bruno PELLETIER d a LSTA & LPMA Université Pierre et Marie Curie – Paris VI Bôıte 158, 175 rue du Chevaleret 75013 Paris, France [email protected] b IRMAR, ENS Cachan Bretagne, CNRS, UEB Campus de Ker Lann Avenue Robert Schuman 35170 Bruz, France [email protected] c University of Delaware Food and Resource Econ...

Semiparametric Estimation of Conditional Heteroscedasticity via Single-index Modeling.

We consider a single-index structure to study heteroscedasticity in regression with high-dimensional predictors. A general class of estimating equations is introduced, the resulting estimators remain consistent even when the structure of the variance function is misspecified. The proposed estimators also possess an adaptive property in an asymptotic sense. That is, they estimate the conditional...