IDEAS home Printed from https://ideas.repec.org/a/spr/coopap/v45y2010i3p521-541.html
   My bibliography  Save this article

A penalized nonparametric method for nonlinear constrained optimization based on noisy data

Author

Listed:
  • Ronaldo Dias
  • Nancy Garcia
  • Adriano Zambom

Abstract

No abstract is available for this item.

Suggested Citation

  • Ronaldo Dias & Nancy Garcia & Adriano Zambom, 2010. "A penalized nonparametric method for nonlinear constrained optimization based on noisy data," Computational Optimization and Applications, Springer, vol. 45(3), pages 521-541, April.
    • Handle: RePEc:spr:coopap:v:45:y:2010:i:3:p:521-541
    DOI: 10.1007/s10589-008-9185-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10589-008-9185-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10589-008-9185-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kooperberg, Charles & Stone, Charles J., 1991. "A study of logspline density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 12(3), pages 327-347, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adriano Zanin Zambom & Brian Seguin & Feifei Zhao, 2019. "Robot path planning in a dynamic environment with stochastic measurements," Journal of Global Optimization, Springer, vol. 73(2), pages 389-410, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kirkby, J. Lars & Leitao, Álvaro & Nguyen, Duy, 2021. "Nonparametric density estimation and bandwidth selection with B-spline bases: A novel Galerkin method," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
    2. Chang, Meng-Shiuh & Wu, Ximing, 2015. "Transformation-based nonparametric estimation of multivariate densities," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 71-88.
    3. Koenker, Roger & Portnoy, Stephen, 2000. "Some pathological regression asymptotics under stable conditions," Statistics & Probability Letters, Elsevier, vol. 50(3), pages 219-228, November.
    4. Richard Spady & Sami Stouli, 2020. "Gaussian Transforms Modeling and the Estimation of Distributional Regression Functions," Papers 2011.06416, arXiv.org.
    5. Koo, Ja-Yong & Kooperberg, Charles, 2000. "Logspline density estimation for binned data," Statistics & Probability Letters, Elsevier, vol. 46(2), pages 133-147, January.
    6. Kwun Chuen Gary Chan & Mei-Cheng Wang, 2017. "Semiparametric Modeling and Estimation of the Terminal Behavior of Recurrent Marker Processes Before Failure Events," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 351-362, January.
    7. Federico Palacios-González & Rosa M. García-Fernández, 2020. "A faster algorithm to estimate multiresolution densities," Computational Statistics, Springer, vol. 35(3), pages 1207-1230, September.
    8. Kyriakos Chourdakis, 2002. "Continuous Time Regime Switching Models and Applications in Estimating Processes with Stochastic Volatility and Jumps," Working Papers 464, Queen Mary University of London, School of Economics and Finance.
    9. Ronaldo Dias & Nancy L. Garcia & Guilherme Ludwig & Marley A. Saraiva, 2015. "Aggregated functional data model for near-infrared spectroscopy calibration and prediction," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(1), pages 127-143, January.
    10. Dias, Ronaldo, 2002. "Nonparametric econometrics," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 22(1), May.
    11. Dias, Ronaldo & Garcia, Nancy L., 2007. "Consistent estimator for basis selection based on a proxy of the Kullback-Leibler distance," Journal of Econometrics, Elsevier, vol. 141(1), pages 167-178, November.
    12. Upmanu Lall & Naresh Devineni & Yasir Kaheil, 2016. "An Empirical, Nonparametric Simulator for Multivariate Random Variables with Differing Marginal Densities and Nonlinear Dependence with Hydroclimatic Applications," Risk Analysis, John Wiley & Sons, vol. 36(1), pages 57-73, January.
    13. Lambert, Philippe, 2021. "Fast Bayesian inference using Laplace approximations in nonparametric double additive location-scale models with right- and interval-censored data," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
    14. Koo, Ja-Yong, 1998. "Convergence Rates for Logspline Tomography," Journal of Multivariate Analysis, Elsevier, vol. 67(2), pages 367-384, November.
    15. Cribari-Neto, Francisco, 1993. "The Cyclical Component in Brazilian GDP," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 13(1), April.
    16. Lopes, Hedibert F. & Dias, Ronaldo, 2011. "Bayesian mixture of parametric and nonparametric density estimation: A Misspecification Problem," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 31(1), March.
    17. Sylvain Sardy & Paul Tseng, 2010. "Density Estimation by Total Variation Penalized Likelihood Driven by the Sparsity ℓ1 Information Criterion," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 321-337, June.
    18. J. S. Marron & S. S. Chung, 2001. "Presentation of smoothers: the family approach," Computational Statistics, Springer, vol. 16(1), pages 195-207, March.
    19. Vincent J. Carey & Carol J. Baker & Richard Platt, 2001. "Bayesian Inference on Protective Antibody Levels Using Case‐Control Data," Biometrics, The International Biometric Society, vol. 57(1), pages 135-142, March.
    20. Bak, Kwan-Young & Jhong, Jae-Hwan & Lee, JungJun & Shin, Jae-Kyung & Koo, Ja-Yong, 2021. "Penalized logspline density estimation using total variation penalty," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:45:y:2010:i:3:p:521-541. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.