Strong Consistency of M-Estimates for the Linear Model.
Abstract
Let (sub 1),...,(sub n),... be i.i.d. observations of a random vector (X,Y) were Y is one-dimensional and X may be multi-dimensional. Suppose that the regression of Y to X, in some sense, is a linear function alpha sub o + beta sub o. It is desired to estimate the unknown parameters alpha sub o, beta sub o, using the observations (sub 1),...(sub n,). A much discussed class of estimates is the so-called M-estimate, which takes the solution of a certain minimization problem as the estimator. Here rho is a properly selected function defined over R' = (infinity). (Keywords: linear models).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1987
- Accession Number
- ADA185487
Entities
People
- X. R. Chen
- Yeuhua Wu
Organizations
- University of Pittsburgh