Identifiability and rates of estimation for scale parameters in location mixture models

• 成果类型: Article
• 署名作者: Ishwaran, H
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1996
• 页码: 1560-1571
• 关键词: convergence

摘要

In this paper we consider the problem of identifiability and estimation for the scale parameter theta in the location mixture model theta(X + Y), where X has a known distribution independent of the YI whose distribution is unknown. Identification of theta is ensured by constraining Y based on the tail behavior of the distribution for X. Rates for estimation are described for those X which can be written as a square summable series of exponential variables. As a special case, our analysis shows that the structural parameters in the Weibull semiparametric mixture (Heckman and Singer) are not estimable at the usual parametric O-p(1/root n) rate. The exact relationship beta-een identifying constraints and achievable rates is explained.