Home | Contents | Submissions, editors, etc. | Login | Search | ECP
 Electronic Journal of Probability > Vol. 11 (2006) > Paper 33 open journal systems 


Weighted uniform consistency of kernel density estimators with general bandwidth sequences

Julia Dony, Free University of Brussels (VUB)
Uwe Einmahl, Free University of Brussels (VUB)


Abstract
Let fn,h be a kernel density estimator of a continuous and bounded d-dimensional density f. Let ψ(t) be a positive continuous function such that ||ψ fβ||<∞ for some 0<β<1/2. We are interested in the rate of consistency of such estimators with respect to the weighted sup-norm determined by ψ. This problem has been considered by Gin, Koltchinskii and Zinn (2004) for a deterministic bandwidth hn. We provide ``uniform in h'' versions of some of their results, allowing us to determine the corresponding rates of consistency for kernel density estimators where the bandwidth sequences may depend on the data and/or the location.


Full text: PDF

Pages: 844-859

Published on: September 24, 2006


Bibliography
  1. Deheuvels, P. (2000). Uniform limit laws for kernel density estimators on possibly unbounded intervals. Recent advances in reliability theory (Bordeaux, 2000), 477--492, Stat. Ind. Technol., Birkhuser Boston, MA. MR1783500
  2. Deheuvels, P. and Mason, D.M. (2004). General asymptotic confidence bands based on kernel-type function estimators. Stat. Inference Stoch. Process. 7(3), 225--277. MR2111291
  3. Einmahl, U. and Mason, D.M. (2000). An empirical process approach to the uniform consistency of kernel-type function estimators. J. Theoret. Probab. 13(1), 1--37. MR1744994
  4. Einmahl, U. and Mason, D.M. (2005). Uniform in bandwidth consistency of kernel-type function estimators. Ann. Statist. 33(3), 1380--1403. MR2195639
  5. Gin, E. and Guillou, A. (2002). Rates of strong uniform consistency for multivariate kernel density estimators. Ann. Inst. H. Poincar Probab. Statist. 38(6), 907--921. MR1955344
  6. Gin, E., Koltchinskii, V. and Sakhanenko, L. (2003). Convergence in distribution of self-normalized sup-norms of kernel density estimators. High dimensional probability, III (Sandjberg, 2002), Progr. Probab., 55, 241--253. Birkhuser, Basel. MR2033892
  7. Gin, E,; Koltchinskii, V. and Sakhanenko, L. (2004). Kernel density estimators: convergence in distribution for weighted sup-norms. Probab. Theory Related Fields, 130(2), 167--198 MR2093761
  8. Gin, E. Koltchinskii, V. and Zinn, J. (2004). Weighted uniform consistency of kernel density estimators. Ann. Probab. 32(3), 2570--2605. MR2078551
  9. Mason, D.M. (2003). Representations for integral functionals of kernel density estimators. Austr. J. Stat., 32(1,2), 131--142.
  10. Pollard, D. (1984). Convergence of stochastic processes. Springer Series in Statistics. Springer-Verlag, New York. MR0762984
  11. Stute, W. (1982). A law of the logarithm for kernel density estimators. Ann. Probab., 10(2), 414--422. MR0647513
  12. Stute, W. (1982). The oscillation behavior of empirical processes. Ann. Probab., 10(1), 86--107. MR0637378
  13. Stute, W. (1984). The oscillation behavior of empirical processes: the multivariate case. Ann. Probab., 12(2), 361--379. MR0735843
  14. Talagrand, M. (1994). Sharper bounds for Gaussian and empirical processes. Ann. Probab. 22(1), 28--76. MR1258865
  15. van der Vaart, A.W. and Wellner, J.A. (1996). Weak convergence and empirical processes. With applications to statistics. Springer Series in Statistics. Springer-Verlag, New York. MR1385671
















Research
Support Tool
Capture Cite
View Metadata
Printer Friendly
Context
Author Address
Action
Email Author
Email Others


Home | Contents | Submissions, editors, etc. | Login | Search | ECP

Electronic Journal of Probability. ISSN: 1083-6489