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Model selection and estimation of a component in additive regression
Let $Y\in\R^n$ be a random vector with mean $s$ and covariance matrix $\sigma^2P_n\tra{P_n}$ where $P_n$ is some known $n\times n$-matrix. We construct a statistical... -
Comparison of procedures for fitting the autoregressive order of a vector err...
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Enhancing the selection of a model-based clustering with external qualitative...
In cluster analysis, it is often useful to interpret the obtained partition with respect to external qualitative variables (defining known partitions) derived from... -
Penalized nonparametric mean square estimation of the coefficients of diffusi...
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A new algorithm for fixed design regression and denoising
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Estimator selection with respect to Hellinger-type risks.
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Estimating composite functions by model selection
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GAUSSIAN MODEL SELECTION WITH AN UNKNOWN VARIANCE
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An Empirical Comparison of V-fold Penalisation and Cross Validation for Model...
Model selection is a crucial issue in machine-learning and a wide variety of penalisation methods (with possibly data dependent complexity penalties) have recently... -
Graph selection with GGMselect
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Learning by mirror averaging
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Estimating a discrete distribution histogram selection
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Studying relationships between environment and malaria incidence in Camopi (F...
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A Posteriori Error Estimation for Subgrid Flamelet Models
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Sharp Oracle Inequalities for Aggregation of Affine Estimators
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Adaptive Covariance Estimation with model selection.
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The Brouwer Lecture 2005: Statistical estimation with model selection
The purpose of this paper is to explain the interest and importance of (approximate) models and model selection in Statistics. Starting from the very elementary... -
Backtesting VaR Accuracy: A New Simple Test
This paper proposes a new test of Value at Risk (VaR) validation. Our test exploits the idea that the sequence of VaR violations (Hit function) - taking value 1-α, if... -
Optimal cross-validation in density estimation
The performance of cross-validation (CV) is analyzed in two contexts: (i) risk estimation and (ii) model selection in the density estimation framework. The main focus... -
Improved penalization for determining the number of factors in approximate fa...
International audience
