IDEAS home Printed from https://ideas.repec.org/p/trn/utwprg/2015-04.html
   My bibliography  Save this paper

A Cross-Entropy approach to the estimation of Generalised Linear Multilevel Models

Author

Listed:
  • Marco Bee
  • Giuseppe Espa
  • Diego Giuliani
  • Flavio Santi

Abstract

In this paper we use the cross-entropy method for noisy optimisation for fitting generalised linear multilevel models through maximum likelihood. We propose specifications of the instrumental distributions for positive and bounded parameters that improve the computational performance. We also introduce a new stopping criterion, which has the advantage of being problem-independent. In a second step we find, by means of extensive Monte Carlo experiments, the most suitable values of the input parameters of the algorithm. Finally, we compare the method to benchmark estimation technique based on numerical integration. The cross-entropy approach turns out to be preferable from both the statistical and the computational point of view. In the last part of the paper, the method is used to model death probability of firms in the healthcare industry in Italy.

Suggested Citation

  • Marco Bee & Giuseppe Espa & Diego Giuliani & Flavio Santi, 2015. "A Cross-Entropy approach to the estimation of Generalised Linear Multilevel Models," DEM Working Papers 2015/04, Department of Economics and Management.
    • Handle: RePEc:trn:utwprg:2015/04
    as

    Download full text from publisher

    File URL: http://web.unitn.it/files/download/39673/demwp2015_04.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rubinstein, Reuven Y., 1997. "Optimization of computer simulation models with rare events," European Journal of Operational Research, Elsevier, vol. 99(1), pages 89-112, May.
    2. Arne Henningsen & Ott Toomet, 2011. "maxLik: A package for maximum likelihood estimation in R," Computational Statistics, Springer, vol. 26(3), pages 443-458, September.
    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. Marco Bee & Maria Michela Dickson & Diego Giuliani & Davide Piacentino & Flavio Santi & Emanuele Taufer, 2016. "La sopravvivenza immediata delle start-up italiane del settore manifatturiero sanitario: un?analisi multilevel," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 49-59.

    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. Maness, Michael & Cirillo, Cinzia, 2016. "An indirect latent informational conformity social influence choice model: Formulation and case study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 75-101.
    2. John-Fritz Thony & Jean Vaillant, 2022. "Parameter Estimation for a Fractional Black–Scholes Model with Jumps from Discrete Time Observations," Mathematics, MDPI, vol. 10(22), pages 1-17, November.
    3. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
    4. K.-P. Hui & N. Bean & M. Kraetzl & Dirk Kroese, 2005. "The Cross-Entropy Method for Network Reliability Estimation," Annals of Operations Research, Springer, vol. 134(1), pages 101-118, February.
    5. Manisera, Marica & Zuccolotto, Paola, 2014. "Modeling rating data with Nonlinear CUB models," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 100-118.
    6. Patelli, Edoardo & Feng, Geng & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "Simulation methods for system reliability using the survival signature," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 327-337.
    7. Fahimnia, Behnam & Sarkis, Joseph & Eshragh, Ali, 2015. "A tradeoff model for green supply chain planning:A leanness-versus-greenness analysis," Omega, Elsevier, vol. 54(C), pages 173-190.
    8. Teresa Backhaus, 2022. "Training in Late Careers - A Structural Approach," CRC TR 224 Discussion Paper Series crctr224_2022_382, University of Bonn and University of Mannheim, Germany.
    9. Ludvík Friebel & Jana Friebelová, 2012. "Stochastic analysis of maintenance process costs in the IT industry: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(3), pages 393-408, September.
    10. Singh, Vijay P. & Oh, Juik, 2015. "A Tsallis entropy-based redundancy measure for water distribution networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 360-376.
    11. Hancock, Thomas O. & Broekaert, Jan & Hess, Stephane & Choudhury, Charisma F., 2020. "Quantum choice models: A flexible new approach for understanding moral decision-making," Journal of choice modelling, Elsevier, vol. 37(C).
    12. Joshua C. C. Chan & Liana Jacobi & Dan Zhu, 2022. "An automated prior robustness analysis in Bayesian model comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 583-602, April.
    13. Granado-Díaz, Rubén & Villanueva, Anastasio J. & Gómez-Limón, José A., 2022. "Willingness to accept for rewilding farmland in environmentally sensitive areas," Land Use Policy, Elsevier, vol. 116(C).
    14. Thoralf Meyer & Paul Holloway & Thomas B. Christiansen & Jennifer A. Miller & Paolo D’Odorico & Gregory S. Okin, 2019. "An Assessment of Multiple Drivers Determining Woody Species Composition and Structure: A Case Study from the Kalahari, Botswana," Land, MDPI, vol. 8(8), pages 1-14, August.
    15. Peter Andre, 2022. "Shallow Meritocracy," CRC TR 224 Discussion Paper Series crctr224_2022_318v3, University of Bonn and University of Mannheim, Germany.
    16. Duc Manh Nguyen & Hoai An Le Thi & Tao Pham Dinh, 2014. "Solving the Multidimensional Assignment Problem by a Cross-Entropy method," Journal of Combinatorial Optimization, Springer, vol. 27(4), pages 808-823, May.
    17. Jens Rommel & Julian Sagebiel & Marieke Cornelia Baaken & Jesús Barreiro‐Hurlé & Douadia Bougherara & Luigi Cembalo & Marija Cerjak & Tajana Čop & Mikołaj Czajkowski & María Espinosa‐Goded & Julia Höh, 2023. "Farmers' risk preferences in 11 European farming systems: A multi‐country replication of Bocquého et al. ()," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(3), pages 1374-1399, September.
    18. Jasmit Shah & Somnath Datta & Susmita Datta, 2014. "A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics," Computational Statistics, Springer, vol. 29(6), pages 1749-1767, December.
    19. Sarrias, Mauricio, 2021. "A two recursive equation model to correct for endogeneity in latent class binary probit models," Journal of choice modelling, Elsevier, vol. 40(C).
    20. N-H Shih, 2005. "Estimating completion-time distribution in stochastic activity networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 744-749, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:trn:utwprg:2015/04. 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: roberto.gabriele@unitn.it (email available below). General contact details of provider: https://edirc.repec.org/data/detreit.html .

    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.