Efficient maximum likelihood estimation in semiparametric mixture models

• 成果类型: Article
• 署名作者: VanderVaart, A
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1996
• 页码: 862-878
• 关键词: parameter; geometry

摘要

We consider maximum likelihood estimation in several examples of semiparametric mixture models, including the exponential frailty model and the errors-in-variables model. The observations consist of a sample of size n from the mixture density integral p(theta)(x\z)d eta(z). The mixing distribution is completely unknown. We show that the first component <(theta(n))over tilde> of the joint maximum likelihood estimator (<(theta(n))over tilde>, <(eta(n))over tilde>) is asymptotically normal and asymptotically efficient in the semiparametric sense.