EFFICIENT ESTIMATION FOR A SUBCLASS OF SHAPE INVARIANT MODELS

• 成果类型: Article
• 署名作者: Vimond, Myriam
• 署名单位: Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/07-AOS566
• 发表日期: 2010
• 页码: 1885-1912
• 关键词: nonlinear-regression; likelihood; CURVES

摘要

In this paper, we observe a fixed number of unknown 2 pi-periodic functions differing from each other by both phases and amplitude. This semiparametric model appears in literature under the name shape invariant model. While the common shape is unknown, we introduce an asymptotically efficient estimator of the unite-dimensional parameter (phases and amplitude) using the profile likelihood and the Fourier basis. Moreover, this estimation method leads to a consistent and asymptotically linear estimator or the common shape.