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ACOMS+ 및 학술지 리포지터리 설명회

  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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A STUDY ON RELATIVE EFFICIENCY OF KERNEL TYPE ESTIMATORS OF SMOOTH DISTRIBUTION FUNCTIONS

한국수학교육학회지시리즈B:순수및응용수학 / Journal of the Korean Society of Mathematical Education Series B: The Pure and Applied Mathematics, (P)1226-0657; (E)2287-6081
1994, v.1 no.1, pp.19-24
Jee, Eun-Sook (Kwangwoon University)
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Abstract

Let P be a probability measure on the real line with Lebesque-density f. The usual estimator of the distribution function (≡df) of P for the sample <TEX>$\chi$</TEX><TEX>$_1$</TEX>,…, <TEX>$\chi$</TEX><TEX>$\_$</TEX>n/ is the empirical df: F<TEX>$\_$</TEX>n/(t)=(equation omitted). But this estimator does not take into account the smoothness of F, that is, the existence of a density f. Therefore, one should expect that an estimator which is better adapted to this situation beats the empirical df with respect to a reasonable measure of performance.(omitted)

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한국수학교육학회지시리즈B:순수및응용수학