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Volumn , Issue , 2008, Pages 273-278

A performance comparison of piecewise linear estimation methods

Author keywords

[No Author keywords available]

Indexed keywords

DATA POINTS; DATA SETS; EMPIRICAL PERFORMANCE; ENGINEERING PROBLEMS; HIGH DIMENSIONAL DATA; HIGH DIMENSIONS; HIGHLY NONLINEAR; IF THERE ARE; LEAST SQUARE; LINEAR FUNCTIONS; MOVING WINDOW; OPTIMAL APPROXIMATION; PERFORMANCE COMPARISON; PIECE-WISE LINEAR FUNCTIONS; PIECEWISE LINEAR; PIECEWISE LINEAR APPROXIMATIONS; PIECEWISE MONOTONIC; PIECEWISE SMOOTH FUNCTIONS; POLYNOMIAL-TIME; POSITIVE INTEGERS; RESPONSE FUNCTIONS; THEORETICAL COMPLEXITY; UNIVARIATE; WEIGHTED LEAST SQUARES;

EID: 65149084603     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1400549.1400587     Document Type: Conference Paper
Times cited : (7)

References (13)
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  • 3
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    • Least squares smoothing of univariate data to achieve piecewise mono-tonicity
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  • 4
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    • Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography
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  • 5
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  • 8
    • 34248351863 scopus 로고    scopus 로고
    • An interpolation method for high dimensional scattered data
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    • M. A. Iyer and L. T. Watson, "An interpolation method for high dimensional scattered data", in Proc. 2006 Spring Simulation Multiconf, Business and Industry Symp., J. A. Hamilton, Jr., R. MacDonald, and M. J. Chinni (eds.), Soc. for Modeling and Simulation Internat, San Diego, CA, 2006, pp. 217-222.
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  • 9
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.