Self-Modelling Warping Functions

Journal of the Royal Statistical Society. Series B: Statistical Methodology - Tập 66 Số 4 - Trang 959-971 - 2004
Daniel Gervini1, Théo Gasser1
1University of Zürich, Switzerland

Tóm tắt

SummaryThe paper introduces a semiparametric model for functional data. The warping functions are assumed to be linear combinations of q common components, which are estimated from the data (hence the name ‘self-modelling’). Even small values of q provide remarkable model flexibility, comparable with nonparametric methods. At the same time, this approach avoids overfitting because the common components are estimated combining data across individuals. As a convenient by-product, component scores are often interpretable and can be used for statistical inference (an example of classification based on scores is given).

Từ khóa


Tài liệu tham khảo

Gasser, 1991, The dynamics of linear growth in distance, velocity and acceleration, Ann. Hum. Biol., 18, 187, 10.1080/03014469100001522

Gasser, 1990, A method for determining the dynamics and intensity of average growth, Ann. Hum. Biol., 17, 459, 10.1080/03014469000001242

Hastie, 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 10.1007/978-0-387-21606-5

Kneip, 1995, Model estimation in nonlinear regression under shape invariance, Ann. Statist., 23, 551, 10.1214/aos/1176324535

Kneip, 1992, Statistical tools to analyze data representing a sample of curves, Ann. Statist., 20, 1266, 10.1214/aos/1176348769

Kneip, 2000, Curve registration by local regression, Can. J. Statist., 28, 19, 10.2307/3315251.n

Ramsay, 1998, Curve registration, J. R. Statist. Soc., 60, 351, 10.1111/1467-9868.00129

Ramsay, 1997, Functional Data Analysis, 10.1007/978-1-4757-7107-7

Ramsay, 2002, Applied Functional Data Analysis

Rønn, 2001, Nonparametric maximum likelihood estimation for shifted curves, J. R. Statist. Soc., 63, 243, 10.1111/1467-9868.00283

van der Vaart, 1998, Asymptotic Statistics, 10.1017/CBO9780511802256

Wang, 1999, Synchronizing sample curves nonparametrically, Ann. Statist., 27, 439

Thông tin
Thông tin xuất bản

Journal of the Royal Statistical Society. Series B: Statistical Methodology

Tập 66 Số 4

959-971

Thông tin tác giả