THE ASYMPTOTIC EFFICIENCY OF CONDITIONAL LIKELIHOOD METHODS
成果类型：
Article
署名作者：
LIANG, KY
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1984
页码：
305313
关键词：
摘要：
The efficiency of the conditional likelihood method for inference in models which include nuisance parameters is examined. A new concept of ancillarity, asymptotic weak ancillarity, is introduced. It is shown that the conditional maximum likelihood estimator and the conditional score test of .theta., the parameter of interest, are asymptotically equivalent to their unconditional counterparts, and hence are asymptotically efficient, provided that the conditioning statistic is asymptotically weakly ancillary. The key assumption that the conditioning statistic is asymptotically weakly ancillary is verified when the underlying distribution is from exponential families. Some illustrative examples are given.