Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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A Comparison Study on the Error Criteria in Nonparametric Regression Estimators

  • Chung, Sung-S. (Division of Mathematics and Statistical Informatics, Chonbuk National University Chonju)
  • Published : 2000.10.31
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Abstract

Most context use the classical norms on function spaces as the error criteria. Since these norms are all based on the vertical distances between the curves, these can be quite inappropriate from a visual notion of distance. Visual errors in Marron and Tsybakov(1995) correspond more closely to "what the eye sees". Simulation is performed to compare the performance of the regression smoothers in view of MISE and the visual error. It shows that the visual error can be used as a possible candidate of error criteria in the kernel regression estimation.

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References

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