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Volumn 12, Issue 3, 2004, Pages 267-274

Regularised kernel density estimation for clustered process data

Author keywords

Deconvolution; Kernel density estimation; Multivariate statistic process control; Probability density function; Regularisation

Indexed keywords

ALGORITHMS; DATA REDUCTION; ESTIMATION; PERSONNEL TRAINING; PROBABILITY DENSITY FUNCTION; REAL TIME SYSTEMS;

EID: 1142268899     PISSN: 09670661     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0967-0661(03)00083-2     Document Type: Article
Times cited : (50)

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  • 2
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    • Chen, Q., Wynne, R., Goulding, P., & Sandoz, D. (2000a). The application of principal component analysis and kernel density estimation to enhance process monitoring. Journal of Control Engineering Practise, 8(5), 531-543.
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    • Chen, Q.1    Wynne, R.2    Goulding, P.3    Sandoz, D.4
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    • 84988123046 scopus 로고
    • Deconvolution with supersmooth distributions
    • Fan, J. (1992). Deconvolution with supersmooth distributions. The Canadian Journal of Statistics, 20, 155-169.
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    • Fan, J.1
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    • Ridge regression: Biased estimation for non-orthogonal problems
    • Hoerl, A. E., & Kennard, R. W. (1970). Ridge regression: Biased estimation for non-orthogonal problems. Technometrics, 12, 55-67.
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    • Hoerl, A.E.1    Kennard, R.W.2
  • 8
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    • Non-parametric confidence bounds for process performance monitoring charts
    • Martin, E. B., & Morris, A. J. (1996). Non-parametric confidence bounds for process performance monitoring charts. Journal of Process Control, 6(6), 349-358.
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    • Orr, M. J. (1995). Regularization in the selection of radial basis function centres. Neural Computation, 7, 606-623.
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    • Multivariate plug-in bandwidth selection
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    • Wand, M.P.1    Jones, M.C.2
  • 14
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    • Finite sample performance of deconvolving density estimators
    • Wand, M. P. (1998). Finite sample performance of deconvolving density estimators. Statistics and Probability Letters, 37, 131-139.
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    • Wand, M.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.