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Warped bases for conditional density estimation
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Selecting the length of a principal curve within a Gaussian model
Principal curves are parameterized curves passing "through the middle" of a data cloud. These objects constitute a way of generalization of the notion of first... -
Histogram selection in non gaussian regression
We deal with the problem of choosing an histogram estimator of a regression function $s$ mapping $\mathcalX$ into $\mathbbR$. We adopt the non asymptotic approach of... -
Selecting Hidden Markov Chain States Number with Cross-Validated Likelihood
The problem of estimating the number of hidden states in a hidden Markov chain model is considered. Emphasis is placed on cross-validated likelihood criteria. Using... -
Model selection for weakly dependent time series forecasting
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A statistical approach for CGH microarray data analysis
Microarray-CGH experiments aim at detecting and mapping chromosomal imbalances, by hybridizing targets of genomic DNA from a test and a reference sample. Probes are... -
Adaptive sequential design for regression on multi-resolution bases
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Detecting Multiple Change-Points in the Mean of Gaussian Process by Model Sel...
This paper deals with the problem of detecting the change-points in mean of a signal corrupted by an additive Gaussian noise. The number of changes and their positions... -
Hidden Markov Models Selection Criteria based on Mean Field-like approximations
Hidden Markov random fields appear naturally in problems such as image segmentation where an unknown class assignment has to be estimated from the observations for... -
Model selection in block clustering by the integrated classification likelihood
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Criteria for longitudinal data model selection based on Kullback's symmetric ...
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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...
