Affordable Access

Publisher Website

Asymptotics of estimators in semi-parametric model under NA samples

Authors
Journal
Journal of Statistical Planning and Inference
0378-3758
Publisher
Elsevier
Publication Date
Volume
136
Issue
10
Identifiers
DOI: 10.1016/j.jspi.2005.01.008
Keywords
  • Semi-Parametric Model
  • Negatively Associated Random Error
  • Least-Square Estimator
  • Consistency
  • Asymptotic Normality
Disciplines
  • Design

Abstract

Abstract This paper is concerned with the heteroscedastic semi-parametric regression model y i = x i β + g ( t i ) + σ i e i , 1 ⩽ i ⩽ n , where σ i 2 = f ( u i ) , ( x i , t i , u i ) are fixed design points, g and f are unknown functions, and random errors e i are negatively associated (NA) random variables. The strong consistency and asymptotic normality for least-squares estimators and weighted least-squares estimators of β are studied. In addition, the strong consistency for the estimators of f ( · ) and g ( · ) is investigated. Some results on independent random error settings are extended.

There are no comments yet on this publication. Be the first to share your thoughts.