An Empirical Study of Indirect Cross-Validation Academic Article uri icon


  • 2011 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. In this paper we provide insight into the empirical properties of indirect cross-validation (ICV), a new method of bandwidth selection for kernel density estimators. First, we describe the method and report on the theoretical results used to develop a practical-purpose model for certain ICV parameters. Next, we provide a detailed description of a numerical study that shows that the ICV method usually outperforms least squares cross-validation (LSCV) in finite samples. One of the major advantages of ICV is its increased stability compared to LSCV. Two real data examples show the benefit of using both ICV and a local version of ICV.

published proceedings

  • Nonparametric Statistics and Mixture Models

author list (cited authors)

  • Savchuk, O., Hart, J., & Sheather, S.

citation count

  • 3

complete list of authors

  • Savchuk, Olga||Hart, Jeffrey||Sheather, Simon

publication date

  • January 2011