Non-parametric regression techniques for biometric problems: Concepts and software

1. Breiman, L. & Friedman, J.H. (1985): Estimating optimal transformations for multiple regression and correlation (with discussion). JASA 80, 580–619.

   MathSciNet  MATH  Google Scholar 

2. Broich, T., Hardle, W. & Krause, A. (1991): XploRe. A computing environment for exploratory Regression and data analysis. Springer, New York.

   Google Scholar 

3. Härdle, W. (1990): Applied nonparametric regression. Cambridge University Press, Cambridge.

   MATH  Google Scholar 

4. Hastie, T. J. & Tibshirani, R. J.(1990): Generalized additive models. Chapman and Hall, London.

   MATH  Google Scholar 

5. Schimek, M. G., (1990): Non-parametric spline regression by BATHSPLINE: Foundations and application. In Faulbaum, F., Haux, R. & Jockel (eds.). SoftStat’89. G. Fischer, Stuttgart, 224–234.

   Google Scholar 

6. Schimek, M. G., Kubik, W. & Schmaranz, K.: The programming of XploRe (in preparation for Statistics and Computing).

   Google Scholar 

7. Silverman, B. W. & Watters, G. W. (1984): BATHSPLINE. An interactive spline smoothing package. University of Bath.

   Google Scholar 

8. Silverman, B. W. (1985). Some aspects of the spline smoothing approach to non-parametric regression curve fitting (with discussion). JRSS B, 47, 1–52.

   MATH  Google Scholar 

9. STATISTICAL SCIENCES, INC. (1990): S-PLUS for DOS. Seattle, Wa.

   Google Scholar 

Download references