Accession Number:

ADA210725

Title:

Asymptotic Robustness in Regression and Autoregression Based on Lindeberg Conditions

Descriptive Note:

Technical rept.

Corporate Author:

STANFORD UNIV CA DEPT OF STATISTICS

Personal Author(s):

Report Date:

1989-06-01

Pagination or Media Count:

36.0

Abstract:

A statistical procedure is asymptotically robust if its large-sample properties hold under conditions more general than the conditions under which the procedure is derived. The justification of such procedures is often based directly or indirectly on a central limit theorem. In this paper Lindeberg-type conditions are utilized to establish asymptotic normality of sample regression and autoregression coefficients.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE