IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v042i11.html
   My bibliography  Save this article

Genetic Optimization Using Derivatives: The rgenoud Package for R

Author

Listed:
  • Mebane Jr., Walter R.
  • Sekhon, Jasjeet S.

Abstract

genoud is an R function that combines evolutionary algorithm methods with a derivative-based (quasi-Newton) method to solve difficult optimization problems. genoud may also be used for optimization problems for which derivatives do not exist. genoud solves problems that are nonlinear or perhaps even discontinuous in the parameters of the function to be optimized. When the function to be optimized (for example, a log-likelihood) is nonlinear in the model's parameters, the function will generally not be globally concave and may have irregularities such as saddlepoints or discontinuities. Optimization methods that rely on derivatives of the objective function may be unable to find any optimum at all. Multiple local optima may exist, so that there is no guarantee that a derivative-based method will converge to the global optimum. On the other hand, algorithms that do not use derivative information (such as pure genetic algorithms) are for many problems needlessly poor at local hill climbing. Most statistical problems are regular in a neighborhood of the solution. Therefore, for some portion of the search space, derivative information is useful. The function supports parallel processing on multiple CPUs on a single machine or a cluster of computers.

Suggested Citation

  • Mebane Jr., Walter R. & Sekhon, Jasjeet S., 2011. "Genetic Optimization Using Derivatives: The rgenoud Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i11).
  • Handle: RePEc:jss:jstsof:v:042:i11
    DOI: http://hdl.handle.net/10.18637/jss.v042.i11
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v042i11/v42i11.pdf
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v042i11/rgenoud_5.7-3.tar.gz
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v042i11/v42i11.R
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v042i11/v42i11-extra.R
    Download Restriction: no

    References listed on IDEAS

    as
    1. Alberto Abadie & Javier Gardeazabal, 2001. "The Economic Costs of Conflict: A Case-Control Study for the Basque Country," NBER Working Papers 8478, National Bureau of Economic Research, Inc.
    2. Braumoeller, Bear F., 2003. "Causal Complexity and the Study of Politics," Political Analysis, Cambridge University Press, vol. 11(03), pages 209-233, June.
    3. Wand, Jonathan & King, Gary & Lau, Olivia, 2011. "anchors: Software for Anchoring Vignette Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i03).
    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. Isabelle Salle & Murat Yıldızoğlu, 2014. "Efficient Sampling and Meta-Modeling for Computational Economic Models," Computational Economics, Springer;Society for Computational Economics, vol. 44(4), pages 507-536, December.
    2. repec:spr:waterr:v:31:y:2017:i:9:d:10.1007_s11269-017-1660-3 is not listed on IDEAS
    3. Isabelle SALLE & Marc-Alexandre SENEGAS & Murat YILDIZOGLU, 2013. "How Transparent About Its Inflation Target Should a Central Bank be? An Agent-Based Model Assessment," Cahiers du GREThA 2013-24, Groupe de Recherche en Economie Théorique et Appliquée.
    4. Chevalier, Clément & Picheny, Victor & Ginsbourger, David, 2014. "KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1021-1034.
    5. Muñoz-Mas, Rafael & Vezza, Paolo & Alcaraz-Hernández, Juan Diego & Martínez-Capel, Francisco, 2016. "Risk of invasion predicted with support vector machines: A case study on northern pike (Esox Lucius, L.) and bleak (Alburnus alburnus, L.)," Ecological Modelling, Elsevier, vol. 342(C), pages 123-134.
    6. Chaeryon Kang & Holly Janes & Ying Huang, 2014. "Combining biomarkers to optimize patient treatment recommendations," Biometrics, The International Biometric Society, vol. 70(3), pages 695-707, September.
    7. Elio Marchione & Shane D Johnson & Alan Wilson, 2014. "Modelling Maritime Piracy: A Spatial Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(2), pages 1-9.
    8. Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2012. "A Robust Method for Estimating Optimal Treatment Regimes," Biometrics, The International Biometric Society, vol. 68(4), pages 1010-1018, December.
    9. Henningsen, Arne & Mpeta, Daniel F. & Adem, Anwar S. & Kuzilwa, Joseph A. & Czekaj, Tomasz G., 2015. "The Effects of Contract Farming on Efficiency and Productivity of Small-Scare Sunflower Farmers in Tanzania," 2015 Conference, August 9-14, 2015, Milan, Italy 212478, International Association of Agricultural Economists.
    10. Alarcón, Silverio & Sánchez, Mercedes, 2016. "Is there a virtuous circle relationship between innovation activities and exports? A comparison of food and agricultural firms," Food Policy, Elsevier, vol. 61(C), pages 70-79.
    11. Henningsen, Arne & Mpeta, Daniel F. & Adem, Anwar S. & Kuzilwa, Joseph A. & Czekaj, Tomasz G., 2015. "A Meta-Frontier Approach for Causal Inference in Productivity Analysis: The Effect of Contract Farming on Sunflower Productivity in Tanzania," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206200, Agricultural and Applied Economics Association;Western Agricultural Economics Association.
    12. repec:eee:ejores:v:266:y:2018:i:1:p:179-192 is not listed on IDEAS
    13. Ummel, Kevin & Fant, Charles, 2014. "Identifying cost-effective deployment strategies through spatiotemporal modelling," WIDER Working Paper Series 121, World Institute for Development Economic Research (UNU-WIDER).
    14. repec:bla:jorssb:v:79:y:2017:i:4:p:1165-1185 is not listed on IDEAS
    15. Anett Weber & Winfried J. Steiner & Stefan Lang, 2017. "A comparison of semiparametric and heterogeneous store sales models for optimal category pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 403-445, March.

    More about this item

    Statistics

    Access and download statistics

    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:jss:jstsof:v:042:i11. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum) or (). General contact details of provider: http://www.jstatsoft.org/ .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.