Jackknifing and bootstrapping quasi–likelihood estimators

Abstract

The properties of several jackknife–based estimators and a bootstrap estimator are investigated in the context of the quasi–likelihood functions. It is shown that often confidence regions based on the usual quasi-likelihood procedures are severely anticonservative, and cannot be trusted. In contrast, a linear and modified linear jackknife have good confidence region properties, being reasonably robust to small sample size, high dispersion, outliers and leverage points.

Keywords:

• Bootstrap percentile confidence interval
• linear jackknife
• leverage point
• outlier
• dispersion parameter
• generalized linear model