Statistical estimation in varying coefficient models

Breiman, L. and Friedman, J. H. (1985). Estimating optimal transformations for multiple regression and correlation (withdiscussion). J. Amer. Statist. Assoc. 80 580-619.

Carroll, R. J., Fan, J., Gijbels, I. and Wand M. P. (1997). Generalized partially linear singleindex models. J. Amer. Statist. Assoc. 92 477-489.

Chen, R. and Tsay, R. S. (1993). Functional-coefficient autoregressive models. J. Amer. Statist. Assoc. 88 298-308.

Cleveland, W. S., Grosse, E. and Shyu, W. M. (1991). Local regression models. In Statistical Models in S (J. M. Chambers, and T. J. Hastie, eds.) 309-376. Wadsworth / Brooks-Cole, Pacific Grove, CA.

Fan, J. and Gijbels, I. (1995). Data-driven bandwidthselection in local polynomial fitting: variable bandwidthand spatial adaptation. J. Roy. Statist. Soc. Ser. B 57 371-394.

Fan, J., H¨ardle, W. and Mammen, E. (1998). Direct estimation of additive and linear components for high dimensional data. Ann. Statist. 26 943-971.

Fan, J. and Zhang, J. (2000). Two-step estimation of functional linear models withapplications to longitudinal data. J. Roy. Statist. Soc. Ser. B 62. To appear.

Friedman, J. H. (1991). Multivariate adaptive regression splines (withdiscussion). Ann. Statist. 19 1-141.

Gu, C. and Wahba, G. (1993). Smoothing spline ANOVA with component-wise Bayesian "confidence intervals." J. Comput. Graph. Statist. 2 97-117.

H¨ardle, W. and Stoker, T. M. (1989). Investigating smooth multiple regression by the method of average derivatives. J. Amer. Statist. Assoc. 84 986-995.

Hastie, T. J. and Tibshirani, R. (1990). Generalized Additive Models. Chapman and Hall, London.

Hastie, T. J. and Tibishirani, R. J. (1993). Varying-coefficient models. J. Roy. Statist. Soc. Ser. B 55, 757-796.

Heckman, J., Ichimura, H., Smith, J. and Todd, P. (1998). Characterizing selection bias using experimental data. Econometrica, 66 1017-1098.

Hoover, D. R., Rice, J. A., Wu, C. O. and Yang, L. P. (1997). Nonparametric smoothing estimates of time-varying coefficient models withlongitudinal data. Biometrika 85 809-822.

Li, K. C. (1991). Sliced inverse regression for dimension reduction (withdiscussion). J. Amer. Statist. Assoc. 86 316-342.

Mack, Y. P., Silverman, B. W. (1982). Weak and Strong uniform consistency of kernel regression estimates. Z. Wahrsch. Verw. Gebiete 61 405-415.

Ruppert, D. (1997). Empirical-bias bandwidths for local polynomial nonparametric regression and density estimation. J. Amer. Statist. Assoc. 92 1049-1062.

Ruppert, D., Sheather, S. J. and Wand, M. P. (1995). An effective bandwidthselector for local least squares regression. J. Amer. Statist. Assoc. 90 1257-1270.

Shumway, R. H. (1988). Apllied Staistical Time Series Analysis. Prentice-Hall, Englewood Cliffs, NJ.

Stone, C. J., Hansen, M., Kooperberg, C. and Truong, Y. K. (1997). Polynomial splines and their tensor products in extended linear modeling. Ann. Statist. 25 1371-1470.

Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions (with discussion). J. Roy. Statist. Soc. Ser. B 36 111-147.

Wahba, G. (1984). Partial spline models for semiparametric estimation of functions of several variables. In Statistical Analysis of Time Series. Proceedings of the Japan-U.S. Joint Seminar, Tokyo 319-329. Institute of Statistical Mathematics, Tokyo.

Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.

Fan, J. and Gijbels, I. (1996). Local Polynomial Modelling and Its Applications. Chapman and Hall, London.

Green, P. J. and Silverman, B. W. (1994). Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach. Chapman and Hall, London.