Robust Optimium Invariant Tests of Covariance Structures Useful in Linear Models.
Abstract
This paper investigates robust optimum invariant tests of some covariance structurs that naturally arise in the context of robustness study in linear models. To describe this concept, let (Y, X beta, sigma sq I) be the assumed (probably incorrect) model while (Y, X beta, sigma sqV) be the correct model, resulting in the specification error in the dispersion matrix. Then it is well known that the BLUEs of all estimable linear parametric function A beta remain the same under both the models if and only if the following condition holds on the structure of V: LX'VZ = 07) where z denotes a matrix of maximal rank satisfying the condition Z'X = 0. Our object is to test the null hypothese that V possesses the structure based on samples on Y under the model (Y, X beta, sigma sq V) for a fixed design matrix X. This hypothesis is of considerable interest as its acceptance greatly simplifies determination of BLUEs of estimable linear parametric functions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 1986
- Accession Number
- ADA174659
Entities
People
- Bimal K. Sinha
- Rita Das
Organizations
- University of Pittsburgh