Sharp oracle inequalities and slope heuristic for specification probabilities estimation in discrete random fields
From MaRDI portal
Publication:5963503
DOI10.3150/14-BEJ660zbMath1342.60077arXiv1106.2467OpenAlexW3103865381WikidataQ98839764 ScholiaQ98839764MaRDI QIDQ5963503
Daniel Y. Takahashi, Matthieu Lerasle
Publication date: 22 February 2016
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1106.2467
Related Items (6)
Estimator selection: a new method with applications to kernel density estimation ⋮ Structure recovery for partially observed discrete Markov random fields on graphs under not necessarily positive distributions ⋮ Estimating the interaction graph of stochastic neural dynamics ⋮ Sparse space-time models: concentration inequalities and Lasso ⋮ Sharp oracle inequalities and slope heuristic for specification probabilities estimation in discrete random fields ⋮ Identifying interacting pairs of sites in Ising models on a countable set
Cites Work
- Unnamed Item
- Optimal model selection in density estimation
- Optimal model selection for density estimation of stationary data under various mixing condi\-tions
- Concentration inequalities and model selection. Ecole d'Eté de Probabilités de Saint-Flour XXXIII -- 2003.
- High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression
- Approximation of density functions by sequences of exponential families
- Gibbs measures and phase transitions
- Risk bounds for model selection via penalization
- A Bennett concentration inequality and its application to suprema of empirical processes
- Optimal model selection in heteroscedastic regression using piecewise polynomial functions
- An oracle approach for interaction neighborhood estimation in random fields
- Identifying interacting pairs of sites in Ising models on a countable set
- Minimal penalties for Gaussian model selection
- Consistent estimation of the basic neighborhood of Markov random fields
- Context tree estimation for not necessarily finite memory processes, via BIC and MDL
- Reconstruction of Markov Random Fields from Samples: Some Observations and Algorithms
- Gaussian model selection
- Sharp oracle inequalities and slope heuristic for specification probabilities estimation in discrete random fields
This page was built for publication: Sharp oracle inequalities and slope heuristic for specification probabilities estimation in discrete random fields