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Rejoinder on: Minimal penalties and the slope heuristics: a survey
Journal de la société française de statistique, Tome 160 (2019) no. 3, pp. 158-168.
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     author = {Arlot, Sylvain},
     title = {Rejoinder on: {Minimal} penalties and the slope heuristics: a survey},
     journal = {Journal de la soci\'et\'e fran\c{c}aise de statistique},
     pages = {158--168},
     publisher = {Soci\'et\'e fran\c{c}aise de statistique},
     volume = {160},
     number = {3},
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     url = {http://archive.numdam.org/item/JSFS_2019__160_3_158_0/}
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Arlot, Sylvain. Rejoinder on: Minimal penalties and the slope heuristics: a survey. Journal de la société française de statistique, Tome 160 (2019) no. 3, pp. 158-168. http://archive.numdam.org/item/JSFS_2019__160_3_158_0/

[1] Arlot, Sylvain; Bach, Francis Data-driven calibration of linear estimators with minimal penalties, 2011 | arXiv

[2] Arlot, Sylvain Minimal penalties and the slope heuristics: a survey, Journal de la SFdS (2019) (arXiv:1901.07277) | MR | Zbl

[3] Baraud, Yannick; Birgé, Lucien Rho-estimators revisited: general theory and applications, Ann. Statist., Volume 46 (2018) no. 6B, pp. 3767-3804 | DOI | MR | Zbl

[4] Baraud, Y.; Birgé, L.; Sart, M. A new method for estimation and model selection: ρ -estimation, Invent. Math., Volume 207 (2017) no. 2, pp. 425-517 | DOI | MR | Zbl

[5] Breiman, Leo Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author), Statist. Sci., Volume 16 (2001) no. 3, pp. 199-231 | DOI | MR | Zbl

[6] Bellec, Pierre C.; Yang, Dana The cost-free nature of optimally tuning Tikhonov regularizers and other ordered smoothers, 2019 (arXiv:1905.12517v1)

[7] Gavish, Matan; Donoho, David L. The Optimal Hard Threshold for Singular Values is 4 / 3 , IEEE Trans. Inform. Theory, Volume 60 (2014) no. 8, pp. 5040-5053 | DOI | MR | Zbl

[8] Garivier, Aurélien; Lerasle, Matthieu Oracle approach and slope heuristic in context tree estimation, 2011 (arXiv:1111.2191v1)

[9] Lerasle, Matthieu Optimal model selection for stationary data under various mixing conditions, Ann. Statist., Volume 39 (2011) no. 4, pp. 1852-1877 | DOI | MR | Zbl

[10] Saumard, Adrien Estimation par Minimum de Contraste Régulier et Heuristique de Pente en Sélection de Modèles, Université de Rennes 1, October (2010) http://tel.archives-ouvertes.fr/tel-00569372/fr/ (Ph. D. Thesis Available at http://tel.archives-ouvertes.fr/tel-00569372v1 )