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A Geometric Programming Framework for Univariate Cubic L 1 Smoothing Splines

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  • Hao Cheng
  • Shu-Cherng Fang
  • John Lavery

Abstract

Univariate cubic L 1 smoothing splines are capable of providing shape-preserving C 1 -smooth approximation of multi-scale data. The minimization principle for univariate cubic L 1 smoothing splines results in a nondifferentiable convex optimization problem that, for theoretical treatment and algorithm design, can be formulated as a generalized geometric program. In this framework, a geometric dual with a linear objective function over a convex feasible domain is derived, and a linear system for dual to primal conversion is established. Numerical examples are given to illustrate this approach. Sensitivity analysis for data with uncertainty is presented. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Hao Cheng & Shu-Cherng Fang & John Lavery, 2005. "A Geometric Programming Framework for Univariate Cubic L 1 Smoothing Splines," Annals of Operations Research, Springer, vol. 133(1), pages 229-248, January.
  • Handle: RePEc:spr:annopr:v:133:y:2005:i:1:p:229-248:10.1007/s10479-004-5035-9
    DOI: 10.1007/s10479-004-5035-9
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    References listed on IDEAS

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    1. Elmor L. Peterson, 1977. "The Duality Between Suboptimization and Parameter Deletion," Discussion Papers 273, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    2. Elmor L. Peterson, 1977. "The Duality between Suboptimization and Parameter Deletion," Mathematics of Operations Research, INFORMS, vol. 2(4), pages 311-319, November.
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    Cited by:

    1. Chiu, Nan-Chieh & Fang, Shu-Cherng & Lavery, John E. & Lin, Jen-Yen & Wang, Yong, 2008. "Approximating term structure of interest rates using cubic L1 splines," European Journal of Operational Research, Elsevier, vol. 184(3), pages 990-1004, February.
    2. Lu, Hao-Chun, 2020. "Indicator of power convex and exponential transformations for solving nonlinear problems containing posynomial terms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    3. Han-Lin Li & Hao-Chun Lu, 2009. "Global Optimization for Generalized Geometric Programs with Mixed Free-Sign Variables," Operations Research, INFORMS, vol. 57(3), pages 701-713, June.
    4. Qingwei Jin & Lu Yu & John Lavery & Shu-Cherng Fang, 2012. "Univariate cubic L 1 interpolating splines based on the first derivative and on 5-point windows: analysis, algorithm and shape-preserving properties," Computational Optimization and Applications, Springer, vol. 51(2), pages 575-600, March.

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