Principal component models for sparse functional data

Biometrika

Volumn 87, Issue 3, 2000, Pages 587-602

  James, Gareth M ^a   Hastie, Trevor J ^b   Sugar, Catherine A ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

Functional data analysis; Growth curve; Mixed effects model; Principal components; Reduced rank estimation

Indexed keywords

EID: 0001699048     PISSN: 00063444     EISSN: None     Source Type: Journal    
DOI: 10.1093/biomet/87.3.587     Document Type: Article

References (17)

1. ANDERSON, T. W. (1951). Estimating linear restrictions on regression coefficients for multivariate normal distributions. Ann. Math. Statist. 22, 327-51.
2. BACHRACH, L., HASTIE, T., WANG, M., NARASIMHAN, B. & MARCUS, R. (1999). Bone mineral acquisition in healthy asian, Hispanic, black and Caucasian youth; a longitudinal study. Clin. Endocrin. Metab. 84, 4702-12.
3. BESSE, C. & CARDOT, H. (1996). Spline approximation of the prediction of a functional autoregressive process of order 1 (in French). Can. J. Statist. 24, 467-87.
4. BESSE, C., CARDOT, H. & FERRATY, F. (1997). Simultaneous non-parametric regressions of unbalanced longitudinal data. Comp. Statist. Data Anal. 24, 255-70.
5. BRUMBACK, B. & RICE, J. (1998). Smoothing spline models for the analysis of nested and crossed samples of curves. J. Am. Statist. Assoc. 93, 961-76.
6. BUCKHEIT, J., OLSHEN, R., BLOUCH, K. & MYERS, B. (1997). Modeling of progressive glomerular injury in humans with lupus nephritis. Am. J. Physiol.-Renal Physiol. 42, F58-69.
7. DEMPSTER, A. P., LAIRD, N. M. & RUBIN, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm (with Discussion). J. R. Statist. Soc. B 39, 1-38.
8. EFRON, B. & TIBSHIRANI, R. (1993). An Introduction to the Bootstrap. London: Chapman and Hall.
9. GASSER, T., MULLER, H.-G., KOHLER, W., MOLINARI, L. & PRADER, A. (1984). Nonparametric regression analysis of growth curves. Ann. Statist. 12, 210-29.
10. GREEN, P. J. & SILVERMAN, B. W. (1994). Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach. London: Chapman and Hall.
11. HENDERSON, C. R. (1950). Estimation of genetic parameters (abstract). Ann. Math. Statist. 21, 309-10.
12. LAIRD, N. & WARE, J. (1982). Random-effects models for longitudinal data. Biometrics 38, 963-74.
13. RAMSAY, J. O. & SILVERMAN, B. W. (1997). Functional Data Analysis. New York: Springer.
14. RICE J. A. & SILVERMAN, B. (1991). Estimating the mean and covariance structure non-parametrically when the data are curves. J. R. Statist. Soc. B 53, 233-43.
15. RICE, J. & Wu, C. (2000). Nonparametric mixed effects models for unequally sampled noisy curves. Biometrics. To appear.
16. SHI, M., WEISS, R. & TAYLOR, J. (1996). An analysis of paediatric cd4 counts for acquired immune deficiency syndrome using flexible random curves. Appl. Statist. 45, 151-64.
17. SILVERMAN, B. W. (1985). Some aspects of the spline smoothing approach to non-parametric regression curve fitting (with Discussion). J. R. Statist. Soc. B 47, 1-52.