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20182025
most citedAsymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes

9 citations · 14 across the 8 of their papers we have counts for

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8 papers · 1 filter

math.ST2025

Inference post region selection

Dominique Bontemps, François Bachoc, Pierre Neuvial

Post-selection inference consists in providing statistical guarantees, based on a data set, that are robust to a prior model selection step on the same data set. In this paper, we…

math.ST2024

Wasserstein Spatial Depth

François Bachoc, Alberto González-Sanz, Jean-Michel Loubes +1

Modeling observations as random distributions embedded within Wasserstein spaces is becoming increasingly popular across scientific fields, as it captures the variability and geome…

math.ST2022

Multivariate Gaussian Random Fields over Generalized Product Spaces involving the Hypertorus

François Bachoc, Ana Peron, Emilio Porcu

The paper deals with multivariate Gaussian random fields defined over generalized product spaces that involve the hypertorus. The assumption of Gaussianity implies the finite dimen…

math.ST20201 cited

Asymptotically Equivalent Prediction in Multivariate Geostatistics

François Bachoc, Emilio Porcu, Moreno Bevilacqua +2

Cokriging is the common method of spatial interpolation (best linear unbiased prediction) in multivariate geostatistics. While best linear prediction has been well understood in un…

math.ST2020

Gaussian linear approximation for the estimation of the Shapley effects

Baptiste Broto, François Bachoc, Marine Depecker +1

In this paper, we address the estimation of the sensitivity indices called "Shapley eects". These sensitivity indices enable to handle dependent input variables. The Shapley eects…

math.ST20199 cited

Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes

François Bachoc, José Bétancourt, Reinhard Furrer +1

The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for n…