Moment properties of estimators for a type 1 extreme-value regression model

Abstract

A regression model is considered in which the response variable has a type 1 extreme-value distribution for smallest values. Bias approximations for the maximum likelihood estimators are pivm and a bias reduction estimator for the scale parameter is proposed. The small sample moment properties of the maximum likelihood estimators are compared with the properties of the ordinary least squares estimators and the best linear unbiased estimators based on order statistics for grouped data.

Keywords:

• type 1 extreme-value regression
• maximum likelihood
• ordinary squares
• best linear unbiased estimation
• bias and mean square error