Variable kernel density estimation

  title={Variable kernel density estimation},
  author={M. Hazelton},
  journal={Australian & New Zealand Journal of Statistics},
  • M. Hazelton
  • Published 2003
  • Mathematics
  • Australian & New Zealand Journal of Statistics
  • Summary This paper considers the problem of selecting optimal bandwidths for variable (sample-point adaptive) kernel density estimation. A data-driven variable bandwidth selector is proposed, based on the idea of approximating the log-bandwidth function by a cubic spline. This cubic spline is optimized with respect to a cross-validation criterion. The proposed method can be interpreted as a selector for either integrated squared error (ISE) or mean integrated squared error (MISE) optimal… CONTINUE READING
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