Measurement Error in Regression Analysis.
Abstract
Consider the linear regression model Y = x theta + epsilon where Y denotes a vector of n observations on the dependent variable, x is a known matrix, theta is a vector of parameters to be estimated and epsilon is a random vector of uncorrelated errors. If X'X is nearly singular, that is if the smallest characteristic root of X'X is small then a small perturbation in the elements of X, such as due to measurement errors, induces considerable variation in the least squares estimate of theta. In this paper we examine for the asymptotic case when n is large the effect of perturbation with regard to the bias and mean squared error fo the estimate. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 08, 1978
- Accession Number
- ADA087287
Entities
People
- Amitava Mitra
- Khursheed Alam
Organizations
- Clemson University