Linear Least Squares Estimates and Nonlinear Means.
Abstract
The consistency and asymptotic normality of a linear least squares estimate of the form (X'X)(bar)X'Y when the mean is not (X)(Beta) is investigated in this paper. The least squares estimate is a consistent estimate of the best linear approximation of the true mean function for the design chosen. The asymptotic normality of the least squares estimate depends on the design and the asymptotic mean may not be the best linear approximation of the true mean function. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1981
- Accession Number
- ADA098169
Entities
People
- Naftali A. Langberg
- Roger L. Berger
Organizations
- Florida State University