Journal of the Korean Statistical Society

  • 제30권2호
  • /
  • Pages.231-246
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  • 2001
  • /
  • 1226-3192(pISSN)
  • /
  • 2005-2863(eISSN)
한국통계학회 (The Korean Statistical Society)
권호 표지

On Adaptation to Sparse Design in Bivariate Local Linear Regression

  • Hall, Peter (Department of Mathematics and Statistics, The Unversity of Western Australia) ;
  • Seifert, Burkhardt (Department of Mathematics and Statistics, The Unversity of Western Australia) ;
  • Turlach, Berwin A. (Department of Mathematics and Statistics, The Unversity of Western Australia)
  • 발행 : 2001.06.01
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초록

Local linear smoothing enjoys several excellent theoretical and numerical properties, an in a range of applications is the method most frequently chosen for fitting curves to noisy data. Nevertheless, it suffers numerical problems in places where the distribution of design points(often called predictors, or explanatory variables) is spares. In the case of univariate design, several remedies have been proposed for overcoming this problem, of which one involves adding additional ″pseudo″ design points in places where the orignal design points were too widely separated. This approach is particularly well suited to treating sparse bivariate design problem, and in fact attractive, elegant geometric analogues of unvariate imputation and interpolation rules are appropriate for that case. In the present paper we introduce and develop pseudo dta rules for bivariate design, and apply them to real data.

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