JOURNAL OF APPLIED STATISTICS, vol.37, no.6, pp.923-943, 2010 (Journal Indexed in SCI)
Article / Article
Title of Journal :
JOURNAL OF APPLIED STATISTICS
correlation coefficient, least squares, linear regression, modified maximum likelihood, multivariate distributions, non-normality, random design, ROBUST ESTIMATION, MAXIMUM-LIKELIHOOD, BINARY REGRESSION, ESTIMATORS, LOCATION
In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.