Optimal design for curve estimation by local linear smoothing

Ming Yen Cheng, Peter Hall*, D. Michael Titterington

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

9 Citations (Scopus)


The integral of the mean squared error of an estimator of a regression function is used as a criterion for defining an optimal design measure in the context of local linear regression, when the bandwidth is chosen in a locally optimal manner. An algorithm is proposed that constructs a sequence of piecewise uniform designs with the help of current estimates of the integral of the mean squared error. These estimates do not require direct estimation of the second derivative of the regression function. Asymptotic properties of the algorithm are established and numerical results illustrate the gains that can be made, relative to a uniform design, by using the optimal design or sub-optimal, piecewise uniform designs. The behaviour of the algorithm in practice is also illustrated.
Original languageEnglish
Pages (from-to)3-14
Number of pages12
Issue number1
Publication statusPublished - Mar 1998

User-Defined Keywords

  • bandwidth choice
  • local linear regression
  • mean squared error
  • nonlinear regression
  • optimal design
  • sequential design


Dive into the research topics of 'Optimal design for curve estimation by local linear smoothing'. Together they form a unique fingerprint.

Cite this