@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://archive.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://archive.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://archive.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://archive.numdam.org/item/JSFS_2019__160_3_154_0/
[1] Model selection for (auto-)regression with dependent data, ESAIM Probab. Statist., Volume 5 (2001), pp. 33-49 | DOI | Numdam | MR | Zbl
[2] Adaptive density estimation for general ARCH models, Econometric Theory, Volume 24 (2008) no. 6, pp. 1628-1662 | DOI | MR | Zbl
[3] Penalized projection estimator for volatility density, Scand. J. Statist., Volume 33 (2006) no. 4, pp. 875-893 | DOI | MR | Zbl
[4] 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] 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] Concentration inequalities and asymptotic results for ratio type empirical processes, Ann.Probab., Volume 33 (2006), pp. 1143-1216 | MR | Zbl
[7] Consistent order estimation and minimal penalties, IEEE Trans. Inform. Theory, Volume 59 (2013) no. 2, pp. 1115-1128 | DOI | MR | Zbl
[8] The local geometry of finite mixtures, Trans. Amer. Math. Soc., Volume 366 (2014) no. 2, pp. 1047-1072 | DOI | MR | Zbl
[9] Strong identifiability and optimal minimax rates for finite mixture estimation, Ann. Statist., Volume 46 (2018) no. 6A, pp. 2844-2870 | DOI | MR | Zbl
[10] 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] Risks bounds for statistical learning, Ann.Stat., Volume 34 (2006) no. 5, pp. 2326-2366 | MR | Zbl
[13] Nonasymptotic quasi-optimality of AIC and the slope heuristics in maximum likelihood estimation of density using histogram models, 2010 (hal-00512310) | arXiv
[14] Finite sample improvement of Akaike’s Information Criterion, arXiv preprint arXiv:1803.02078 (2018)