Bigot, Jérémie Escande, Paul Weiss, Pierre

We provide a new estimator of integral operators with smooth kernels, obtained from a set of scattered and noisy impulse responses. The proposed approach relies on the formalism of smoothing in reproducing kernel Hilbert spaces and on the choice of an appropriate regularization term that takes the smoothness of the operator into account. It is nume...

Chen, Yuting Cournède, Paul-Henry
Published in
Ecological Modelling

A three-step data assimilation approach is proposed in this paper to enhance crop model predictive capacity in various environmental conditions. The most influential parameters are first selected by global sensitivity analysis and then estimated in a Bayesian framework. The posterior distribution of the estimation step is then considered as prior i...

Roche, Angelina

In more and more applications, a quantity of interest may depend on several covariates, with at least one of them infinite-dimensional (e.g. a curve). To select relevant covariate in this context, we propose an adaptation of the Lasso method. The criterion is based on classical Lasso inference under group sparsity (Yuan and Lin, 2006; Lounici et al...

Chatelain, Jean-Bernard Ralf, Kirsten

A number of macroeconomic theories, very popular in the 1980s, seem to have completely disappeared and been replaced by the dynamic stochastic general equilibrium (DSGE) approach. We will argue that this replacement is due to a tacit agreement on a number of assumptions, previously seen as mutually exclusive, and not due to a settlement by 'nature'...

Dion, Charlotte Hermann, Simone Samson, Adeline

Stochastic differential equations (SDEs) are useful to model continuous stochastic processes. When (independent) repeated temporal data are available, variability between the trajectories can be modeled by introducing random effects in the drift of the SDEs. These models are useful to analyse neuronal data, crack length data, pharmacokinetics, fina...

LOUM, Mor Absa Poursat, Marie-Anne Sow, Abdourahmane Sall, Amadou Loucoubar, Cheikh Gassiat, Elisabeth

In tropical regions, populations continue to suffer morbidity and mortality from malaria and arboviral diseases. In Kedougou (Senegal), these illnesses are all endemic due to the climate and its geographical position. The co-circulation of malaria parasites and arboviruses can explain the observation of coinfected cases. Indeed there is strong rese...

Ahidar-Coutrix, Adil Le Gouic, Thibaut Paris, Quentin

This paper provides rates of convergence for empirical barycentres of a Borel probability measure on a metric space under general conditions. Our results are given in the form of sharp oracle inequalities. Our main assumption, of geometrical nature, is shown to be satisfied at least in two meaningful scenarios. The first one is a form of weak curva...

Caron, Emmanuel

In this paper, we consider the usual linear regression model in the case where the error process is assumed strictly stationary. We use a result from Hannan (1973), who proved a Central Limit Theorem for the usual least square estimator under general conditions on the design and on the error process. Whatever the design satisfying Hannan's conditio...

Caron, E. Dede, S.
Published in
Mathematical Methods of Statistics

We consider the usual linear regression model in the case where the error process is assumed strictly stationary.We use a result of Hannan, who proved a Central Limit Theorem for the usual least squares estimator under general conditions on the design and the error process.We show that for a large class of designs, the asymptotic covariance matrix ...

Lerasle, Matthieu Szabó, Zoltán Lecué, Guillaume Massiot, Gaspar Moulines, Eric

Mean embeddings provide an extremely flexible and powerful tool in machine learning and statistics to represent probability distributions and define a semi-metric (MMD, maximum mean discrepancy ; also called N-distance or energy distance), with numerous successful applications. The representation is constructed as the expectation of the feature map...