Strong Consistency and Exponential Rate of the 'Minimum L1-Norm' Estimates in Linear Regression Models.
Abstract
This document considers a linear regression model, where (x sub i) is a sequence of experimental points, i. e., known p-vectors, (e sub i) is a sequence of independent random errors, with med(e sub i) =0,i= 1,2....Define the minimum L1 -norm estimate of (alpha, beta)', by (alpha, beta)', to be chosen such that under quite general conditions on (x sub i) and (e sub i), the strong consistency of the minimum L1 -norm estimate is established. Further, under an additional condition on (x sub i), it is also proved that for any given epsilon > 0, there exist constant C > O not depending on n.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 1987
- Accession Number
- ADA185695
Entities
People
- Yuehua Wu
Organizations
- University of Pittsburgh