ONE-SIDED ESTIMATING AND TESTING PROBLEMS FOR LOCATION MODELS FROM GROUPED SAMPLES

Abstract

This article deals with one-sided problems for location models from grouped samples. Suppose the support region of a density function, which does not depend on parameters, is divided into some disjointed intervals, grouped samples are the number of observations falling in each intervals respectively. The studying of grouped samples may be dated back to the beginning of the century, in which only one sample location and/or scale models is considered. This article considers one-sided estimating and testing problems for location models. Some methods for computing the maximum likelihood estimates of the parameters subject to order restrictions are proposed and a numerical example by the method is given.

Keywords:

• Grouped samples
• Restricted maximum likelihood estimation
• Location models

ACKNOWLEDGMENTS

The project is supported by the National Natural Science Foundation of China and the authors extend their appreciations to referees for their helpful comments.