Clustering for sparsely sampled functional data

Journal of the American Statistical Association

Volumn 98, Issue 462, 2003, Pages 397-408

  James, Gareth M ^a   Sugar, Catherine A ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Curve estimation; Discriminant functions; Functional clustering; High dimensional data

Indexed keywords

EID: 0043245795     PISSN: 01621459     EISSN: None     Source Type: Journal    
DOI: 10.1198/016214503000189     Document Type: Article

References (22)

1. Bachrach, L. K., Hastie, T. J., Wang, M. C., Narasimhan, B., and Marcus, R. (1999), "Bone Mineral Acquisition in Healthy Asian, Hispanic, Black and Caucasian Youth: A Longitudinal Study," Journal of Clinical Endocrinology & Metabolism, 84, 4702-4712.
2. Banfield, J. D., and Raftery, A. E. (1993), "Model-Based Gaussian and Non-Gaussian Clustering," Biometrics, 49, 803-821.
3. Celeux, G., and Govaert, G. (1995), "Gaussian Parsimonious Clustering Models," The Journal of the Pattern Recognition Society, 28, 781-793.
4. Dasgupta, A., and Raftery, A. E. (1998), "Detecting Features in Spatial Point Processes with Clutter via Model-Based Clustering," Journal of the American Statistical Association, 93, 294-302.
5. de Boor, C. (1978), A Practical Guide to Splines, New York: Springer.
6. DiPillo, P. J. (1976), "The Application of Bias to Discriminant Analysis," Communications in Statistics, Part A - Theory and Methods, A5, 843-854.
7. Friedman, J. H. (1989), "Regularized Discriminant Analysis," Journal of the American Statistical Association, 84, 165-175.
8. Green, P. J., and Silverman, B. W. (1994), Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach, London: Chapman and Hall.
9. Hartigan, J. A., and Wong, M. A. (1978), "Algorithm AS 136: A k-Means Clustering Algorithm," Applied Statistics, 28, 100-108.
10. Hastie, T. J., Buja, A., and Tibshirani, R. J. (1995), "Penalized Discriminant Analysis," Annals of Statistics, 23, 73-102.
11. James, G. M., and Hastie, T. J. (2001), "Functional Linear Discriminant Analysis for Irregularly Sampled Curves," Journal of the Royal Statistical Society, Ser. B, 63, 533-550.
12. James, G. M., Hastie, T. J., and Sugar, C. A. (2000), "Principal Component Models for Sparse Functional Data," Biometrika, 87, 587-602.
13. Kass, R. E., and Raftery, A. E. (1995), "Bayes Factors," Journal of the American Statistical Association, 90, 773-795.
14. Kaufman, L., and Rousseeuw, P. (1990), Finding Groups in Data: An Introduction to Cluster Analysis, New York: Wiley.
15. Murtagh, F., and Raftery, A. E. (1984), "Fitting Straight Lines to Point Patterns," Pattern Recognition, 17, 479-483.
16. O'Sullivan, F. (1985), "A Statistical Perspective on Ill-Posed Inverse Problems," Statistical Science, 1, 502-527.
17. Rice, J. A., and Wu, C. O. (2001), "Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves," Biometrics, 57, 253-259.
18. Schwarz, G. (1978), "Estimating the Dimension of a Model," The Annals of Statistics, 6, 461-464.
19. Sugar, C. A., and James, G. M. (2003), "Choosing the Number of Clusters: An Information Theoretic Approach," Journal of the American Statistical Association, (To Appear).
20. Titterington, D. M. (1985), "Common Structure of Smoothing Techniques in Statistics," International Statistical Review, 53, 141-170.
21. Wald, P. W., and Kronmal, R. A. (1977), "Discriminant Functions When Covariances Are Unequal and Sample Sizes Moderate," Biometrics, 33, 479-484.
22. Ward, J. H. (1963), "Hierarchical Groupings to Optimize an Objective Function," Journal of the American Statistical Association, 58, 234-244.