2004, English, Article, Journal or magazine article edition: On Gauss quadrature and partial cross validation Kozek, A. S; Yin, J

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Bookmark: http://trove.nla.gov.au/version/49527479
Physical Description
  • journal article
Published
  • Elsevier, 2004
Language
  • English

Edition details

Title
  • On Gauss quadrature and partial cross validation
Author
  • Kozek, A. S
  • Yin, J
Other Contributors
  • Macquarie University. Department of Statistics
Published
  • Elsevier, 2004
Physical Description
  • journal article
Subjects
Summary
  • New estimators of expected values Ew(X) of functions of a random variable X are introduced. The new estimators are based on Gauss quadrature, a numerical method frequently used to approximate integrals over finite intervals. The estimators need a small number of numerical evaluations and hence are useful in partial cross validation (PCV) a numerical method for finding optimal smoothing parameters in nonparametric curve estimation. The PCV can considerably reduce the computational cost of the generalized cross validation method typically used to determine the optimal smoothing parameter.
  • 18 page(s)
Language
  • English
Related Resource
  • Computational statistics &​ data analysis, Vol. 45, Issue 3, p.431-448
  • 10.1016/​S0167-9473(03)00040-9
Identifier
  • mq:691
  • ISSN:1872-7352
  • mq-rm-2004022315

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