Corrected Maximum Likelihood in Non-Regular Problems
针对三参数威布尔或伽马分布等非正则情形下最大似然估计失效的问题，提出修正似然函数的方法，使估计效果令人满意。
SUMMARY Maximum likelihood (ML) estimation can break down for distributions like the three-parameter Weibull or gamma where one of the parameters is a limit of the range of the distribution. It is suggested that use of the product of densities for the likelihood function is a misapplication of the ML method in such non-regular cases, and that this is the reason for its failure. It is shown that ML works quite satisfactorily if the likelihood is corrected in an appropriate way.