Discussion
Discussion on “Minimal penalties and the slope heuristic: a survey” by Sylvain Arlot
[Discussion sur « Pénalités minimales et heuristique de pente » par Sylvian Arlot]
Journal de la société française de statistique, Tome 160 (2019) no. 3, pp. 154-157.
@article{JSFS_2019__160_3_154_0,
     author = {Saumard, Adrien},
     title = {Discussion on {{\textquotedblleft}Minimal} penalties and the slope heuristic: a survey{\textquotedblright} by {Sylvain} {Arlot}},
     journal = {Journal de la soci\'et\'e fran\c{c}aise de statistique},
     pages = {154--157},
     publisher = {Soci\'et\'e fran\c{c}aise de statistique},
     volume = {160},
     number = {3},
     year = {2019},
     mrnumber = {4021421},
     zbl = {1431.62129},
     language = {en},
     url = {http://www.numdam.org/item/JSFS_2019__160_3_154_0/}
}
TY  - JOUR
AU  - Saumard, Adrien
TI  - Discussion on “Minimal penalties and the slope heuristic: a survey” by Sylvain Arlot
JO  - Journal de la société française de statistique
PY  - 2019
SP  - 154
EP  - 157
VL  - 160
IS  - 3
PB  - Société française de statistique
UR  - http://www.numdam.org/item/JSFS_2019__160_3_154_0/
LA  - en
ID  - JSFS_2019__160_3_154_0
ER  - 
%0 Journal Article
%A Saumard, Adrien
%T Discussion on “Minimal penalties and the slope heuristic: a survey” by Sylvain Arlot
%J Journal de la société française de statistique
%D 2019
%P 154-157
%V 160
%N 3
%I Société française de statistique
%U http://www.numdam.org/item/JSFS_2019__160_3_154_0/
%G en
%F JSFS_2019__160_3_154_0
Saumard, Adrien. Discussion on “Minimal penalties and the slope heuristic: a survey” by Sylvain Arlot. Journal de la société française de statistique, Tome 160 (2019) no. 3, pp. 154-157. http://www.numdam.org/item/JSFS_2019__160_3_154_0/

[1] Baraud, Y.; Comte, F.; Viennet, G. Model selection for (auto-)regression with dependent data, ESAIM Probab. Statist., Volume 5 (2001), pp. 33-49 | DOI | Numdam | MR | Zbl

[2] Comte, F.; Dedecker, J.; Taupin, M. L. Adaptive density estimation for general ARCH models, Econometric Theory, Volume 24 (2008) no. 6, pp. 1628-1662 | DOI | MR | Zbl

[3] Comte, F.; Genon-Catalot, V. Penalized projection estimator for volatility density, Scand. J. Statist., Volume 33 (2006) no. 4, pp. 875-893 | DOI | MR | Zbl

[4] Comte, F.; Lacour, C.; Rozenholc, Y. Adaptive estimation of the dynamics of a discrete time stochastic volatility model, J. Econometrics, Volume 154 (2010) no. 1, pp. 59-73 | DOI | MR | Zbl

[5] Comte, F.; Rozenholc, Y. Adaptive estimation of mean and volatility functions in (auto-)regressive models, Stochastic Process. Appl., Volume 97 (2002) no. 1, pp. 111-145 | DOI | MR | Zbl

[6] Giné, E.; Koltchinskii, V. Concentration inequalities and asymptotic results for ratio type empirical processes, Ann.Probab., Volume 33 (2006), pp. 1143-1216 | MR | Zbl

[7] Gassiat, E.; van Handel, R. Consistent order estimation and minimal penalties, IEEE Trans. Inform. Theory, Volume 59 (2013) no. 2, pp. 1115-1128 | DOI | MR | Zbl

[8] Gassiat, E.; van Handel, R. The local geometry of finite mixtures, Trans. Amer. Math. Soc., Volume 366 (2014) no. 2, pp. 1047-1072 | DOI | MR | Zbl

[9] Heinrich, P.; Kahn, J. Strong identifiability and optimal minimax rates for finite mixture estimation, Ann. Statist., Volume 46 (2018) no. 6A, pp. 2844-2870 | DOI | MR | Zbl

[10] Koltchinskii, V. Oracle inequalities in empirical risk minimization and sparse recovery problems, Lecture Notes in Mathematics, 2033, Springer, Heidelberg, 2011, x+254 pages (Lectures from the 38th Probability Summer School held in Saint-Flour, 2008, École d’Été de Probabilités de Saint-Flour. [Saint-Flour Probability Summer School]) | MR | Zbl

[11] Massart, P.; Nédélec, E. Risks bounds for statistical learning, Ann.Stat., Volume 34 (2006) no. 5, pp. 2326-2366 | MR | Zbl

[13] Saumard, A. Nonasymptotic quasi-optimality of AIC and the slope heuristics in maximum likelihood estimation of density using histogram models, 2010 (hal-00512310) | arXiv

[14] Saumard, A.; Navarro, F. Finite sample improvement of Akaike’s Information Criterion, arXiv preprint arXiv:1803.02078 (2018)