next up previous
Next: About this document ... Up: ASSIST: A Suite of Previous: Future Research

Bibliography

Andrews, D. F. and Herzberg, A. M. (1985).

Data: A Collection of Problems From Many Fields for the Student and Research Worker, Springer:Brln:NY.

Arendt, J., Mirors, D. S. and Waterhouse, J. M. (1989).

Biological rhythms in clinical practice, Wright, London.

Aronszajn, N. (1950).

Theory of reproducing kernels, Trans. Amer. Math. Soc. 68: 337-404.

Bates, D. M., Lindstrom, M. J., Wahba, G. and Yandell, B. S. (1987).

GCVPACK: Routines for generalized cross validation, CommStB 16: 263-297.

Craven, P. and Wahba, G. (1979).

Smoothing noisy data with spline functions, Numer. Math. 31: 377-403.

Dette, H., Munk, A. and Wagner, T. (1998).

Estimating the variance in nonparametric regression - what is a reasonable choice?, Journal of the Royal Statistical Society B 60: 751-764.

Donoho, D. L. and Johnston, I. M. (1994).

Ideal spatial adaption by wavelet shrinkage, Biometrika 81: 425-456.

Earn, D. J. D., Rohani, P., Bolker, B. M. and Gernfell, B. T. (2000).

A simple model for complex dynamical transitions in epidemics, Science 287: 667-670.

Eubank, R. (1988).

Spline Smoothing and Nonparametric Regression, New York: Dekker.

Gasser, T., Sroka, L. and Jennen-Steinmetz, C. (1986).

Residual variance and residual pattern in nonlinear regression, Biometrika 73: 625-633.

Green, P. J. and Silverman, B. W. (1994).

Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach, London: Chapman and Hall.

Grizzle, J. E. and Allen, D. M. (1969).

Analysis of growth and dose response curves, Biometrics 25: 357-381.

Gu, C. (1989).

RKPACK and its applications: Fitting smoothing spline models, Proceedings of the Statistical Computing Section, ASA: pp. 42-51.

Gu, C. (1990).

Adaptive spline smoothing in non-Gaussian regression models, Journal of the American Statistical Association 85: 801-807.

Gu, C. (1992).

Cross-validating non Gaussian data, Journal of Computational and Graphical Statistics 2: 169-179.

Gu, C. (2002).

Smoothing Spline ANOVA Models, Springer-Verlag, New York.

Gu, C. and Wahba, G. (1991).

Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method, SIAM J. Sci. Stat. Comput. 12: 383-398.

Gu, C. and Wahba, G. (1993a).

Semiparametric ANOVA with tensor product thin plate spline, Journal of the Royal Statistical Society B 55: 353-368.

Gu, C. and Wahba, G. (1993b).

Smoothing spline ANOVA with component-wise Bayesian confidence intervals, Journal of Computational and Graphical Statistics 2: 97-117.

Hall, P., Kay, J. W. and Titterington, D. M. (1990).

Asymptotically optimal difference-based estimation of variance in nonparametric regression, Biometrika 77: 521-528.

Hall, P., Reimann, J. and Rice, J. (2001).

Nonparametric estimation of a periodic function, Biometrika 87: 545-557.

Hastie, T. and Tibshirani, R. (1990).

Generalized Additive Models, Chapman and Hall.

Hastie, T. and Tibshirani, R. (1993).

Varying coefficient model, Journal of the Royal Statistical Society B 55: 757-796.

Heckman, N. and Ramsay, J. O. (2000).

Penalized regression with model-based penalties, Canadian Journal of Statistics 28: 241-258.

Karcher, P. and Wang, Y. (2002).

Generalized nonparametric mixed effects models, Journal of Computational and Graphical Statistics 10: 641-655.

Ke, C. and Wang, Y. (2001).

Semi-parametric nonlinear mixed effects models and their applications (with discussion), Journal of the American Statistical Association 96: 1272-1298.

Ke, C. and Wang, Y. (2002).

Nonparametric nonlinear regression models, Technical Report # 385, Department of Statistics and Applied Probability, University of California - Santa Barbara.

Kitagawa, G. and Gersch, W. (1984).

A smoothness priors-state space modeling of time series with trend and seasonality, Journal of the American Statistical Association 79: 378-389.

Klein, R., Klein, B. E. K., Moss, S. E., Davis, M. D. and DeMets, D. L. (1988).

Glycosylated hemoglobin predicts the incidence and progression of diabetic retinopathy, Journal of the American Medical Association 260: 2864-2871.

Kronfol, Z., Nair, M., Zhang, Q., Hill, E. and Brown, M. (1997).

Circadian immune measures in healthy volunteers: Relationship to hypothalamic-pituitary-adrenal axis hormones and sympathetic neurotransmitters, Psychosomatic Medicine 59: 42-50.

Lawton, W. H., Sylvestre, E. A. and Maggio, M. S. (1972).

Self-modeling nonlinear regression, Technometrics 13: 513-532.

Liu, A. and Wang, Y. (2004).

Hypothesis testing in smoothing spline models, Journal of Statistical Computation and Simulation.

Liu, A., Meiring, W. and Wang, Y. (2004).

Testing generalized linear models using smoothing spline methods, Statistica Sinica 14: 000-000.

Nychka, D. (1988).

Bayesian confidence intervals for smoothing splines, Journal of the American Statistical Association 83: 1134-1143.

Nychka, D. and Ruppert, D. (1995).

A nonparametric transformation applied to both sides of a regression model, Journal of the Royal Statistical Society B 57: 519-532.

Opsomer, J., Wang, Y. and Yang, Y. (2001).

Nonparametric regression with correlated errors, Statistical Science 16: 134-153.

O'Sullivan, F. (1990).

Convergence characteristics of methods of regularization estimators for nonlinear operator equations, SIAM Journal on Numerical Analysis 27: 1635-1649.

O'Sullivan, F. (1991).

Sensitivity analysis for regularized estimation in some system identification problems, SIAM J. Sci. Stat. Comput. 12: 1266-1283.

O'Sullivan, F. and Wahba, G. (1985).

A cross validated Bayesian retrieval algorithm for non-linear remote sensing, J. Comput. Phys. 59: 441-455.

Pinheiro, J. and Bates, D. M. (2000).

Mixed-effects Models in S and S-plus, Springer, New York.

Potvin, C., Lechowicz, M. J. and Tardif, S. (1990).

The statistical analysis of ecophysiological response curves obtained from experiments involving repeated measures, Ecology 71: 1389-1400.

Ramsay, J. O. (1998).

Estimating smooth monotone functions, Journal of the Royal Statistical Society B 60: 365-375.

Ramsay, J. O. and Li, X. (1998).

Curve registration, Journal of the Royal Statistical Society B 60: 351-363.

Ramsay, J. O. and Silverman, B. W. (1997).

Functional Data Analysis, Springer, New York.

Refinetti, R. (1993).

Laboratory instrumentation and computing: Comparison of six methods for the determination of the period of circadian rhythms, Physiology and Behavior 54: 869-875.

Rice, J. A. (1984).

Bandwidth choice for nonparametric regression, Annals of Statistics 12: 1215-1230.

Roosen, C. and Hastie, T. (1994).

Automatic smoothing spline projection pursuit, Journal of Computational and Graphical Statistics 3: 235-248.

Schaffer, W. and Kot, M. (1985).

Nearly one dimensional dynamics in an epidemic, Journal of Theoretical Biology 112: 403-427.

Self, S. G. and Liang, K.-Y. (1987).

Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions, Journal of the American Statistical Association 82: 605-610.

Simonoff, J. (1996).

Smoothing Methods in Statistics, Springer-Verlag, New York.

Venables, W. N. and Ripley, B. D. (1998).

Modern Applied Statistics With S-Plus, Springer, New York.

Wahba, G. (1978).

Improper priors, spline smoothing, and the problem of guarding against model errors in regression, Journal of the Royal Statistical Society B 40: 364-372.

Wahba, G. (1981).

Spline interpolation and smoothing on the sphere, SIAM J. Sci. Stat. Comput. 2: 5-16.

Wahba, G. (1982).

Erratum: Spline interpolation and smoothing on the sphere, SIAM J. Sci. Stat. Comput. 3: 385-386.

Wahba, G. (1983).

Bayesian confidence intervals for the cross-validated smoothing spline, Journal of the Royal Statistical Society B 45: 133-150.

Wahba, G. (1987).

Three topics in ill posed inverse problems, Inverse and Ill-Posed Problems, M. Engl and G. Groetsch, eds., Academic Press.

Wahba, G. (1990).

Spline Models for Observational Data, SIAM, Philadelphia.
CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 59.

Wahba, G. and Luo, Z. (1996).

Smoothing spline ANOVA fits for vary large, nearly regular data sets, with application to historical global climate data, Festschrift in Honor of Ted Rivlin, C. Micchelli, Ed.

Wahba, G. and Wang, Y. (1993).

Behavior near zero of the distribution of GCV smoothing parameter estimates for splines, Statistics and Probability Letters 25: 105-111.

Wahba, G., Wang, Y., Gu, C., Klein, R. and Klein, B. (1995).

Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy, Annals of Statistics 23: 1865-1895.

Wang, Y. (1997).

GRKPACK: fitting smoothing spline analysis of variance models to data from exponential families, Communications in Statistics: Simulation and Computation 26: 765-782.

Wang, Y. (1998a).

Mixed-effects smoothing spline ANOVA, Journal of the Royal Statistical Society B 60: 159-174.

Wang, Y. (1998b).

Smoothing spline models with correlated random errors, Journal of the American Statistical Association 93: 341-348.

Wang, Y. and Brown, M. B. (1996).

A flexible model for human circadian rhythms, Biometrics 52: 588-596.

Wang, Y. and Wahba, G. (1995).

Bootstrap confidence intervals for smoothing splines and their comparison to Bayesian confidence intervals, J. Statist. Comput. Simul. 51: 263-279.

Wang, Y. and Wahba, G. (1998).

Discussion of "Smoothing Spline Models for the Analysis of Nested and Crossed Samples of Curves" by Brumback and Rice, Journal of the American Statistical Association 93: 976-980.

Wang, Y., Guo, W. and Brown, M. B. (2000).

Spline smoothing for bivariate data with applications to association between hormones, Statistica Sinica 10: 377-397.

Wang, Y., Wahba, G., Chappell, R. and Gu, C. (1995).

Simulation studies of smoothing parameter estimates and Bayesian confidence intervals in Bernoulli SS ANOVA models, Communications in Statistics: Simulation and Computation 24: 1037-1059.

Wang, Y., Wahba, G., Gu, C., Klein, R. and Klein, B. (1997).

Using smoothing spline ANOVA to examine the relation of risk factors to the incidence and progression of diabetic retinopathy, Statistics in Medicine 16: 1357-1376.

Yorke, J. and London, W. (1973).

Recurrent outbreaks of measles, chickenpox and mumps, American Journal of Epidemiology 98: 453-482.



Yuedong Wang 2004-05-19