Journal of Statistics: Advances in Theory and Applications[1] A. Antoniadis, J. Bigot and I. Gijbels, Penalized wavelet monotone
regression, Statist. Prob. Lett. 77(16) (2007), 1608-1621.
[2] G. Beliakov and M. Kohler, Estimation of regression functions by
Lipschitz continuous functions, Submitted for publication, 2005.
[3] A. Beresteanu, Nonparametric estimation of regression functions
under restrictions on partial derivatives, Rand. Journal of Economics,
2005.
[4] R. Blundell and A. Duncan, Kernel regression in empirical
microeconomics, Journal of Human Resources, Winter 33(1) (1998),
62-87.
[5] D. Bosq and J. P. Lecoutre, Théorie de l´estimation
fonctionnelle, Economica, Paris, 1987.
[6] O. Bousquet, S. Boucheron and G. Lugosi, Theory of classification:
A survey of some recent advancement, ESAIM: Probability and Statistics
9 (2005), 323-375.
[7] K. L. Chung, A Course in Probability Theory, Third edition,
Academic Press, New York, 2001.
[8] G. Collomb, Estimation non-paraétrique de la régression: Revue
bibliographique, Inter. Statist. Rev. 49 (1981), 75-93.
[9] G. Collomb, Propiétés de convergence presque compléte du
prédicteur à noyan, Zeitung Wahrscheinlichkeitstheorie und verwandte
Gebiete 66 (1984), 441-460.
[10] G. Collomb, Nonparametric regression: An up to date bibliography,
Statistics 2 (1985), 297-307.
[11] S. Döhler and L. Rüschendorf, Nonparametric estimation of
regression functions in point process models, Statistical Inference
for Stochastic Processes 6(3) (2003), 291-307.
[12] J. Fajardo, R. Ríos and L. Rodríguez, Properties of convergence
of a fuzzy set estimator of the density function, Submitted for
publication, 2010.
[13] M. Falk and F. Liese, Lan of thinned empirical processes with an
application to fuzzy set density estimation, Extremes 1(3) (1998),
323-349, Seminare Maurey-Schwartz (1975-1976).
[14] F. Ferraty, A. Mas and P. Vieu, Nonparametric regression on
functional data: Inference and practical aspects, Aust. N. Z. J.
Statist. 10.1111/j.1467-842X. 2006.00467.x, 2007.
[15] F. Ferraty, V. Núnez-Antón and P. Vieu, Regresión No
Paramétrica: Desde la Dimensión uno Hasta la Dimensión Infinita,
Servicio Editorial de la Universidad del Pais Vasco, Bilbao, 2001.
[16] P. Hall, Q. Li and J. Racine, Nonparametric estimation of
regression functions in the presence of irrelevant regressors, Review
of Economics and Statistics 89 (2007), 784-789.
[17] W. Härdle, Applied Nonparametric Regression, Cambridge Univ.
Press, Cambridge, 1990.
[18] W. Härdle, Smoothing Techniques with Implementation in S,
Springer Verlag, New York, 1991.
[19] C. Ludeña and R. Ríos, Teoría de Aprendizaje Estadístico y
Selección de Modelos, Decimosexta Escuela Venezolana de Matemáticas,
Mérida-Venezuela, 2003.
[20] P. Massart, Some applications of concentration inequalities to
statistics, probability theory, Annales de la Faculté des Sciences de
Toulouse (2) (2000), 245-303.
[21] J. Racine and Q. Li, Nonparametric estimation of regression
functions with both categorical and continuous data, Journal of
Econometrics 119 (2004), 99-130.
[22] M. Schimek, Smoothing and Regression: Approaches, Computation,
and Application, M. G. Schimek (ed.), Wiley Series in Probability
and Statistics, Wiley, New York, 2000.
[23] C. Stone, Optimal rates of convergence for nonparametric
regression, Ann. Statist. (9) (1981), 1348-1360.
[24] A. W. Van der Vaart and J. A. Wellner, Weak Convergence and
Empirical Processes: With Applications to Statistics, Springer
Series in Statistic, Springer-Verlag, New York, Inc., 1996.
[25] M. P. Wand and M. C. Jones, Kernel Smoothing, Chapman Hall,
London, 1995.
[26] A. Watson, Estudio Comparativo de Diversos Métodos de
Estimación de Densidades por Kernels, Master’s thesis, Universidad
Simón Bolívar, Caracas-Venezuela, 2007.
