Confidence Bounds for the Linear Model of Less than the Full Rank with an Introduction to G-Inverses
Abstract
This paper explains the use of Scheffe's theorem on simultaneous confidence bounds in the context of linear hypothesis model of less than the full rank. In paving the background, some results on the uniqueness of estimates in the theory of singular designs are brought together in a compact form in this report with a brief explanatory introduction to the solution of linear equations as related to the computation of a g-inverse.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1980
- Accession Number
- ADA086094
Entities
People
- Kali S. Banerjee
Organizations
- Ballistic Research Laboratory