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Comments on: Inference and computation with Generalized Additive Models and their extensions

Author

Listed:
  • Sonja Greven

    (Humboldt-Universität zu Berlin)

  • Fabian Scheipl

    (LMU Munich)

Abstract

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  • Sonja Greven & Fabian Scheipl, 2020. "Comments on: Inference and computation with Generalized Additive Models and their extensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 343-350, June.
    • Handle: RePEc:spr:testjl:v:29:y:2020:i:2:d:10.1007_s11749-020-00714-2
    DOI: 10.1007/s11749-020-00714-2
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    References listed on IDEAS

    as
    1. Cederbaum, Jona & Scheipl, Fabian & Greven, Sonja, 2018. "Fast symmetric additive covariance smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 25-41.
    2. Christos Argyropoulos & Mark L Unruh, 2015. "Analysis of Time to Event Outcomes in Randomized Controlled Trials by Generalized Additive Models," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-33, April.
    3. Simon N. Wood & Zheyuan Li & Gavin Shaddick & Nicole H. Augustin, 2017. "Generalized Additive Models for Gigadata: Modeling the U.K. Black Smoke Network Daily Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1199-1210, July.
    4. Rajen D. Shah & Richard J. Samworth, 2013. "Variable selection with error control: another look at stability selection," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(1), pages 55-80, January.
    5. Sarah Brockhaus & Andreas Fuest & Andreas Mayr & Sonja Greven, 2018. "Signal regression models for location, scale and shape with an application to stock returns," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 665-686, April.
    6. Sonja Greven & Thomas Kneib, 2010. "On the behaviour of marginal and conditional AIC in linear mixed models," Biometrika, Biometrika Trust, vol. 97(4), pages 773-789.
    7. David Rügamer & Sarah Brockhaus & Kornelia Gentsch & Klaus Scherer & Sonja Greven, 2018. "Boosting factor‐specific functional historical models for the detection of synchronization in bioelectrical signals," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 621-642, April.
    8. Ryan J. Tibshirani & Jonathan Taylor & Richard Lockhart & Robert Tibshirani, 2016. "Exact Post-Selection Inference for Sequential Regression Procedures," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 600-620, April.
    9. Simon N. Wood & Natalya Pya & Benjamin Säfken, 2016. "Smoothing Parameter and Model Selection for General Smooth Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1548-1563, October.
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    Keywords

    62-08; 62J05; 62J99; 62G08; 62G99; 62P99;
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