EXISTENCE OF MAXIMUM-LIKELIHOOD-ESTIMATES FOR INTERVAL-CENSORED DATA FROM SOME 3-PARAMETER MODELS WITH A SHIFTED ORIGIN

• 成果类型: Article
• 署名作者: NAKAMURA, T
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• 发表日期: 1991
• 页码: 211-220
• 关键词: regression-models; unimodality; uniqueness; parameter

摘要

Given data in the form of interval-censored observations from a three-parameter distribution, practical criteria are established for the existence of maximum likelihood estimates for three kinds of parameter space. These criteria can be derived by analysing the behaviour of the log-likelihood near a type of boundary of the parameter space, called the probability contents inner boundary. The effectiveness of the criteria is discussed. In the case where the underlying distribution is a three-parameter log-normal distribution, the efficiency of the criteria is evaluated by simulation.