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Volumn 1, Issue 1, 1991, Pages 47-62

Computational methods for local regression

Author keywords

blending function; k d tree; loess; Nonparametric regression; semi parametric model

Indexed keywords


EID: 33847166455     PISSN: 09603174     EISSN: 15731375     Source Type: Journal    
DOI: 10.1007/BF01890836     Document Type: Article
Times cited : (236)

References (35)
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    • Breiman, L. (to appear) The II method for estimating multivariate functions from noisy data. Technometrics.
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    • Ethanol fuel—a single-cylinder engine study of efficiency and exhaust emissions
    • (1981) SAE Transactions , vol.90 , Issue.no. 810345 , pp. 1410-1424
    • Brinkman, N.D.1
  • 11
    • 84936324764 scopus 로고    scopus 로고
    • Cleveland, W. S. and Grosse, E. (in press) Fitting Functions to Data, Wadsworth, Pacific Grove, Calif.
  • 27
    • 84936339311 scopus 로고    scopus 로고
    • Gu, C. and Wahba, G. (1988) Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method. Technical Report 847. Department of Statistics, University of Wisconsin.
  • 34
    • 0000450226 scopus 로고
    • Improper priors, spline smoothing, and the problem of guarding against model errors in regression
    • (1978) J. R. Stat. Soc. B , vol.40 , pp. 364-372
    • Wahba, G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.