IDEAS home Printed from https://ideas.repec.org/e/pnu24.html
   My authors  Follow this author

Laura Marta Nuñez Letamendia

Personal Details

First Name:Laura
Middle Name:Marta
Last Name:Nuñez Letamendia
Suffix:
RePEc Short-ID:pnu24
Serrano 105, 28006 Madrid, Spain
+34915689647

Affiliation

IE Business School
Universidad IE

Madrid, Spain
http://www.ie.edu/es/business-school/

: +34 91 568 96 00

María de Molina, 11. 28006 Madrid
RePEc:edi:inempes (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Laura Nuñez, 2005. "Predicción de la insolvencia empresarial: uso de búsqueda tabú para selección de ratios explicativos," Working Papers Economia wpe05-34, Instituto de Empresa, Area of Economic Environment.
  2. Laura Nuñez, 2004. "The problem of variable selection for financial distress: applying GRASP methaeuristics," Working Papers Economia wp04-30, Instituto de Empresa, Area of Economic Environment.
  3. Laura Nuñez, 2004. "Do Moving Average Rules Make Profits? A Study Using The Madrid Stock Market," Working Papers Economia wp04-03, Instituto de Empresa, Area of Economic Environment.
  4. NUÑEZ, Laura, 2002. "An analysis of the robustness of Genetic Algorithm (GA) methodology in the design of trading systems for the Stock Exchange," Computing in Economics and Finance 2002 29, Society for Computational Economics.
  5. Laura Nuñez, 2002. "An Analysis Of The Robustness Of Genetic Algorithm (ga) Methodology In The Design Of Trading System," Working Papers Economia wp02-24, Instituto de Empresa, Area of Economic Environment.

Articles

  1. Pacheco, Joaquín & Casado, Silvia & Núñez, Laura, 2009. "A variable selection method based on Tabu search for logistic regression models," European Journal of Operational Research, Elsevier, vol. 199(2), pages 506-511, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Pacheco, Joaquín & Casado, Silvia & Núñez, Laura, 2009. "A variable selection method based on Tabu search for logistic regression models," European Journal of Operational Research, Elsevier, vol. 199(2), pages 506-511, December.

    Cited by:

    1. Brusco, Michael J. & Steinley, Douglas, 2011. "Exact and approximate algorithms for variable selection in linear discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 123-131, January.
    2. Pacheco, Joaquín & Casado, Silvia & Porras, Santiago, 2013. "Exact methods for variable selection in principal component analysis: Guide functions and pre-selection," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 95-111.
    3. Aytug, Haldun, 2015. "Feature selection for support vector machines using Generalized Benders Decomposition," European Journal of Operational Research, Elsevier, vol. 244(1), pages 210-218.
    4. García-Alonso, Carlos R. & Torres-Jiménez, Mercedes & Hervás-Martínez, César, 2010. "Income prediction in the agrarian sector using product unit neural networks," European Journal of Operational Research, Elsevier, vol. 204(2), pages 355-365, July.
    5. Unler, Alper & Murat, Alper, 2010. "A discrete particle swarm optimization method for feature selection in binary classification problems," European Journal of Operational Research, Elsevier, vol. 206(3), pages 528-539, November.
    6. Fouskakis, D., 2012. "Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods," European Journal of Operational Research, Elsevier, vol. 220(2), pages 414-422.
    7. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    8. Toshiki Sato & Yuichi Takano & Ryuhei Miyashiro & Akiko Yoshise, 2016. "Feature subset selection for logistic regression via mixed integer optimization," Computational Optimization and Applications, Springer, vol. 64(3), pages 865-880, July.
    9. Lingras, P. & Butz, C.J., 2010. "Rough support vector regression," European Journal of Operational Research, Elsevier, vol. 206(2), pages 445-455, October.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 4 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CMP: Computational Economics (3) 2003-10-20 2005-07-25 2005-07-25
  2. NEP-FMK: Financial Markets (3) 2003-10-20 2005-07-25 2005-07-25
  3. NEP-FIN: Finance (2) 2003-10-20 2005-07-25
  4. NEP-CFN: Corporate Finance (1) 2005-07-25
  5. NEP-FOR: Forecasting (1) 2005-07-25
  6. NEP-RMG: Risk Management (1) 2003-10-20

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Laura Marta Nuñez Letamendia should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can 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.