論文

査読有り
2018年7月

Generalised gamma kernel density estimation for nonnegative data and its bias reduction

Journal of Nonparametric Statistics
  • Igarashi, Gaku
  • ,
  • Kakizawa, Yoshihide

30
3
開始ページ
598
終了ページ
639
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1080/10485252.2018.1457791
出版者・発行元
Taylor and Francis

We consider density estimation for nonnegative data using generalised gamma density. What is being emphasised here is that a negative exponent is allowed. We show that, for each positive or negative exponent, (i) generalised gamma kernel density estimator, without bias reduction, has the mean integrated squared error (MISE) of order O(n-4/5), as in other boundary-bias-free density estimators from the existing literature, and that (ii) the bias-reduced versions have the MISEs of order O(n-4/5), where n is the sample size. We illustrate the finite sample performance of the proposed estimators through the simulations.

リンク情報
DOI
https://doi.org/10.1080/10485252.2018.1457791
ID情報
  • DOI : 10.1080/10485252.2018.1457791
  • ISSN : 1048-5252

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