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Editorial on the special issue on the V Latin American conference on statistical computing

Author

Listed:
  • David Fernando Muñoz

    (Instituto Tecnológico Autónomo de México
    Universidad Nacional Agraria La Molina)

  • Verónica Andrea González-López

    (University of Campinas)

  • Jürgen Symanzik

    (Utah State University)

Abstract

No abstract is available for this item.

Suggested Citation

  • David Fernando Muñoz & Verónica Andrea González-López & Jürgen Symanzik, 2025. "Editorial on the special issue on the V Latin American conference on statistical computing," Computational Statistics, Springer, vol. 40(6), pages 2849-2856, July.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:6:d:10.1007_s00180-025-01644-z
    DOI: 10.1007/s00180-025-01644-z
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    References listed on IDEAS

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    1. Meng Li & Sijia Xiang & Weixin Yao, 2016. "Robust estimation of the number of components for mixtures of linear regression models," Computational Statistics, Springer, vol. 31(4), pages 1539-1555, December.
    2. Armando Tapia & Silvestre L. González & Jose R. Vergara & Mariano Villafuerte & Luis V. Montiel, 2025. "Policy evaluation using model over-fitting: the Nordic case," Computational Statistics, Springer, vol. 40(6), pages 2955-2980, July.
    3. Nuno M. Brites & Carlos A. Braumann, 2025. "Moments and probability density of threshold crossing times for populations in random environments under sustainable harvesting policies," Computational Statistics, Springer, vol. 40(6), pages 3191-3203, July.
    4. Alba Martinez-Ruiz & Natale Carlo Lauro, 2025. "Incremental singular value decomposition for some numerical aspects of multiblock redundancy analysis," Computational Statistics, Springer, vol. 40(6), pages 3291-3319, July.
    5. Gustavo Di-Giorgi & Rodrigo Salas & Rodrigo Avaria & Cristian Ubal & Harvey Rosas & Romina Torres, 2025. "Volatility forecasting using deep recurrent neural networks as GARCH models," Computational Statistics, Springer, vol. 40(6), pages 3229-3255, July.
    6. Daniel Arreola & Luis V. Montiel, 2024. "Approximating income inequality dynamics given incomplete information: an upturned Markov chain model," Computational Statistics, Springer, vol. 39(2), pages 629-651, April.
    7. Weichang Kong & Fei Qiao & Qidi Wu, 2020. "Real-manufacturing-oriented big data analysis and data value evaluation with domain knowledge," Computational Statistics, Springer, vol. 35(2), pages 515-538, June.
    8. Natalia da Silva & Dianne Cook & Eun-Kyung Lee, 2025. "Interactive graphics for visually diagnosing forest classifiers in R," Computational Statistics, Springer, vol. 40(6), pages 3105-3125, July.
    9. Carlos García & Zaida Quiroz & Marcos Prates, 2023. "Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima–Peru," Computational Statistics, Springer, vol. 38(2), pages 603-621, June.
    10. Marco Antonio Montufar-Benítez & Jaime Mora-Vargas & Carlos Arturo Soto-Campos & Gilberto Pérez-Lechuga & José Raúl Castro-Esparza, 2025. "A simulation model to analyze the behavior of a faculty retirement plan: a case study in Mexico," Computational Statistics, Springer, vol. 40(6), pages 2981-3006, July.
    11. Mohammad Kazemi & Paulo Canas Rodrigues, 2025. "Robust singular spectrum analysis: comparison between classical and robust approaches for model fit and forecasting," Computational Statistics, Springer, vol. 40(6), pages 3257-3289, July.
    12. Luísa Novais & Susana Faria, 2025. "Robust order selection of mixtures of regression models with random effects," Computational Statistics, Springer, vol. 40(6), pages 3205-3228, July.
    13. Mario Vazquez Corte & Luis V. Montiel, 2025. "Novel matrix hit and run for sampling polytopes and its GPU implementation," Computational Statistics, Springer, vol. 40(6), pages 3067-3104, July.
    14. Carlos Rondero-Guerrero & Isidro González-Hernández & Carlos Soto-Campos, 2025. "An extended approach for the generalized powered uniform distribution," Computational Statistics, Springer, vol. 40(6), pages 2907-2930, July.
    15. Eduardo S. B. Oliveira & Mário Castro & Cristian L. Bayes & Jorge L. Bazán, 2025. "Bayesian quantile regression models for heavy tailed bounded variables using the No-U-Turn sampler," Computational Statistics, Springer, vol. 40(6), pages 3007-3040, July.
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