On a Unified Theory of Estimation in Linear Models
PURDUE UNIV LAFAYETTE IN DEPT OF STATISTICS
Pagination or Media Count:
In a series of papers the author developed two approaches towards a unified treatment of the General Gauss-Markoff GGM linear model Y, X beta, sigma squared V where V, the dispersion matrix of Y, may be singular and X may be deficient in rank. One is called the inverse partition IPM method which depends on the numerical evaluation of a g-inverse of a partitioned matrix. Another is an analogue of least square theory and is called unified least square ULS method. The aim of the paper is to bring out the salient features of these two methods and to point out some interesting features of linear unbiased estimation when the dispersion matrix of the observations is singular.
- Statistics and Probability