IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v47y2004i2p211-223.html
   My bibliography  Save this article

Applications of optimization heuristics to estimation and modelling problems

Author

Listed:
  • Winker, Peter
  • Gilli, Manfred

Abstract

No abstract is available for this item.

Suggested Citation

  • Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
    • Handle: RePEc:eee:csdana:v:47:y:2004:i:2:p:211-223
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(03)00271-8
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
    2. Baragona, R. & Battaglia, F. & Cucina, D., 2004. "Fitting piecewise linear threshold autoregressive models by means of genetic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 277-295, September.
    3. Fortemps, Ph. & Ost, Ch. & Pirlot, M. & Teghem, J. & Tuyttens, D., 1996. "Using metaheuristics for solving a production scheduling problem in a chemical firm. A case study," International Journal of Production Economics, Elsevier, vol. 46(1), pages 13-26, December.
    4. Schlottmann, Frank & Seese, Detlef, 2004. "A hybrid heuristic approach to discrete multi-objective optimization of credit portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 373-399, September.
    5. Wu, Berlin & Chang, Chih-Li, 2002. "Using genetic algorithms to parameters (d,r) estimation for threshold autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 38(3), pages 315-330, January.
    6. Chatterjee, Sangit & Laudato, Matthew & Lynch, Lucy A., 1996. "Genetic algorithms and their statistical applications: an introduction," Computational Statistics & Data Analysis, Elsevier, vol. 22(6), pages 633-651, October.
    7. Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
    8. H. D. Vinod & B. D. McCullough, 1999. "The Numerical Reliability of Econometric Software," Journal of Economic Literature, American Economic Association, vol. 37(2), pages 633-665, June.
    9. Pacheco, Joaquin & Valencia, Olga, 2003. "Design of hybrids for the minimum sum-of-squares clustering problem," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 235-248, June.
    10. Angelis, L. & Bora-Senta, E. & Moyssiadis, C., 2001. "Optimal exact experimental designs with correlated errors through a simulated annealing algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 37(3), pages 275-296, September.
    11. Todorov, Valentin, 1992. "Computing the minimum covariance determinant estimator (MCD) by simulated annealing," Computational Statistics & Data Analysis, Elsevier, vol. 14(4), pages 515-525, November.
    12. Woodruff, David L. & Reiners, Torsten, 2004. "Experiments with, and on, algorithms for maximum likelihood clustering," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 237-253, September.
    13. Ferri, M. & Piccioni, M., 1992. "Optimal selection of statistical units : An approach via simulated annealing," Computational Statistics & Data Analysis, Elsevier, vol. 13(1), pages 47-61, January.
    14. H. D. Vinod & B. D. McCullough, 1999. "Corrigenda: The Numerical Reliability of Econometric Software," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1565-1565, December.
    15. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    16. Luebke, Karsten & Weihs, Claus, 2004. "Generation of prediction optimal projection on latent factors by a stochastic search algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 297-310, September.
    17. Duczmal, Luiz & Assuncao, Renato, 2004. "A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 269-286, March.
    18. Ostermark, Ralf, 2001. "Genetic modelling of multivariate EGARCHX-processes: evidence on the international asset return signal response mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 38(1), pages 71-93, November.
    19. Baragona, Roberto & Battaglia, Francesco & Calzini, Claudio, 2001. "Genetic algorithms for the identification of additive and innovation outliers in time series," Computational Statistics & Data Analysis, Elsevier, vol. 37(1), pages 1-12, July.
    20. Roverato, Alberto & Paterlini, Sandra, 2004. "Technological modelling for graphical models: an approach based on genetic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 323-337, September.
    21. Maringer, Dietmar G., 2004. "Finding the relevant risk factors for asset pricing," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 339-352, September.
    22. Alcock, Jamie & Burrage, Kevin, 2004. "A genetic estimation algorithm for parameters of stochastic ordinary differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 255-275, September.
    23. Sung Jung, Joo & Jin Yum, Bong, 1996. "Construction of exact D-optimal designs by tabu search," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 181-191, February.
    24. Winker, Peter, 1995. "Identification of multivariate AR-models by threshold accepting," Computational Statistics & Data Analysis, Elsevier, vol. 20(3), pages 295-307, September.
    25. Dorsey, Robert E & Mayer, Walter J, 1995. "Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 53-66, January.
    26. Besbeas, Panagiotis & Morgan, Byron J. T., 2004. "Integrated squared error estimation of normal mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 44(3), pages 517-526, January.
    27. Orsenigo, Carlotta & Vercellis, Carlo, 2004. "Discrete support vector decision trees via tabu search," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 311-322, September.
    28. Cadima, Jorge & Cerdeira, J. Orestes & Minhoto, Manuel, 2004. "Computational aspects of algorithms for variable selection in the context of principal components," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 225-236, September.
    29. Birchenhall, Chris, 1995. "Modular Technical Change and Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 8(3), pages 233-253, August.
    Full references (including those not matched with items on IDEAS)

    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. Manfred GILLI & Peter WINKER, 2008. "A review of heuristic optimization methods in econometrics," Swiss Finance Institute Research Paper Series 08-12, Swiss Finance Institute.
    2. Francesco Battaglia & Mattheos K. Protopapas, 2010. "Multi-regime models for nonlinear nonstationary time series," Working Papers 026, COMISEF.
    3. Kapetanios, George, 2007. "Variable selection in regression models using nonstandard optimisation of information criteria," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 4-15, September.
    4. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    5. Francesco Battaglia & Mattheos Protopapas, 2012. "An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 315-334, August.
    6. Francesco Battaglia & Mattheos K. Protopapas, 2011. "Time‐varying multi‐regime models fitting by genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 237-252, May.
    7. Schleer, Frauke, 2013. "Finding starting-values for maximum likelihood estimation of vector STAR models," ZEW Discussion Papers 13-076, ZEW - Leibniz Centre for European Economic Research.
    8. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
    9. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2004. "Estimating threshold subset autoregressive moving-average models by genetic algorithms," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 39-61.
    10. Max Jerrell, 2000. "Applications Of Public Global Optimization Software To Difficult Econometric Functions," Computing in Economics and Finance 2000 161, Society for Computational Economics.
    11. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    12. Lars Vilhuber, 2024. "Report of the AEA Data Editor," AEA Papers and Proceedings, American Economic Association, vol. 114, pages 878-890, May.
    13. Sexton, Randall S. & Dorsey, Robert E. & Johnson, John D., 1999. "Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing," European Journal of Operational Research, Elsevier, vol. 114(3), pages 589-601, May.
    14. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.
    15. F. Javier Mencía & Enrique Sentana, 2004. "Estimation and Testing of Dynamic Models with Generalised Hyperbolic Innovations," Working Papers wp2004_0411, CEMFI.
    16. Manfred Gilli & Enrico Schumann, 2012. "Heuristic optimisation in financial modelling," Annals of Operations Research, Springer, vol. 193(1), pages 129-158, March.
    17. Jeffrey S. Zax, 2002. "Comment on “Estimating the Extent of Racially Polarized Voting in Multicandidate Contests†by Bernard Grofman and Michael Migalski," Sociological Methods & Research, , vol. 31(1), pages 75-86, August.
    18. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    19. Mencía, Javier & Sentana, Enrique, 2009. "Multivariate location-scale mixtures of normals and mean-variance-skewness portfolio allocation," Journal of Econometrics, Elsevier, vol. 153(2), pages 105-121, December.
    20. Vinod, H. D., 2001. "Care and feeding of reproducible econometrics," Journal of Econometrics, Elsevier, vol. 100(1), pages 87-88, January.

    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:eee:csdana:v:47:y:2004:i:2:p:211-223. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.