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題 名 | Beta Kernel Smoothers for Regression Curves |
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作 者 | Chen,Song Xi; | 書刊名 | Statistica Sinica |
卷 期 | 10:1 2000.01[民89.01] |
頁 次 | 頁73-91 |
分類號 | 319.51 |
關鍵詞 | 局部線性迴歸; 回歸曲線; Beta kernels; Boundary bias; Local linear regression; Mean integrated square error; Nonparametric regression; |
語 文 | 英文(English) |
英文摘要 | This paper proposes beta kernel smoothers for estimating curves with compact support by employing a beta family of densities as kernels. These beta kernel smoothers are free of boundary bias, achieve the optimal convergence rate of n-4/5 for mean integrated squared error and always allocate non-negative weights. In the context of regression, a comparison is made between one of the beta smoothers and the local linear smoother. Its mean integrated squared error is comparable with that of the local linear smoother. Situations where the beta kernel smoother has a smaller mean integrated squared error are given. Extensions to probability density estimation are discussed. |
本系統中英文摘要資訊取自各篇刊載內容。