Recherche - Laboratoire Jean Kuntzmann

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Laboratoire Jean Kuntzmann
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		Three Alternatives to the Likelihood Maximization for Estimating a Centered Matérn (3/2) Process Didier A. Girard 2015 Article de blog scientifique hal-01957338v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimating a Centered Ornstein-Uhlenbeck Process under Measurement Errors Didier A. Girard 2014 Article de blog scientifique hal-02009088v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimating a Centered Matérn (1) Process: Three Alternatives to Maximum Likelihood via Conjugate Gradient Linear Solvers Didier A. Girard 2015 Article de blog scientifique hal-01957409v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		An experimental assessment of the "Gibbs-Energy and Empirical-Variance" estimating equations (via Kalman smoothing) for Matérn processes Didier A. Girard Quatrièmes rencontres R (4th R meeting ), Jun 2015, Grenoble, France Communication dans un congrès hal-01229334v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimators of a Noisy Centered Ornstein-Uhlenbeck Process and Its Noise Variance Didier A. Girard 2018 Article de blog scientifique hal-02009103v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Curve Estimation by Smoothing Splines: Unbiased-Risk-Estimate Selector and its Robust Version via Randomized Choices Didier A. Girard 2017 Article de blog scientifique hal-01957175v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Density Estimation: Robust Cross-Validation Bandwidth Selection via Randomized Choices Didier A. Girard 2018 Article de blog scientifique hal-01957055v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Additive Modeling by Smoothing Splines: Robust Unbiased-Risk-Estimate Selector and a Nonisotropic-Smoothing Improvement Didier A. Girard 2017 Article de blog scientifique hal-01957225v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimating a centered AR1xAR1 Gaussian field by likelihood maximization or GE-EV matching Didier A. Girard 2023 Article de blog scientifique hal-04302799v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Implémentation en R d'une alternative ("CGEM-EV") au maximum de vraisemblance pour des champs de type Matérn Didier A. Girard [Rapport Technique] LJK. 2011 Rapport hal-00648526v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Efficiently estimating some common geostatistical models by ‘energy–variance matching’ or its randomized ‘conditional–mean’ versions Didier A. Girard Spatial Statistics, 2017, 21, Part A, pp.1-26. ⟨10.1016/j.spasta.2017.01.001⟩ Article dans une revue hal-00515832v4	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimation non-paramétrique de courbes (ou surfaces ou images): vers des régions de confiance pour l'estimateur (localement) L2-optimal Didier A. Girard 2010 Pré-publication, Document de travail hal-00450049v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Curve Estimation by Kernel Smoothers under Correlated Errors Didier A. Girard 2021 Article de blog scientifique hal-03349695v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Asymptotic near-efficiency of the "Gibbs-energy (GE) and empirical-variance" estimating functions for fitting Matérn models - II: Accounting for measurement errors via "conditional GE mean Didier A. Girard Statistics and Probability Letters, 2020, Statistics and Probability Letters, 162, pp.108726:1-11. ⟨10.1016/j.spl.2020.108726⟩ Article dans une revue hal-00413693v3	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Regression and Kernel Smoothing: Confidence Regions for the L2-Optimal Curve Estimate Didier A. Girard 2013 Article de blog scientifique hal-00854307v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Nonparametric Curve Estimation by Kernel Smoothers: Efficiency of Unbiased Risk Estimate and GCV Selectors Didier A. Girard 2013 Article de blog scientifique hal-00854223v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Estimating the accuracy of (local) cross-validation via randomised GCV choices in kernel or smoothing spline regression Didier A. Girard Journal of Nonparametric Statistics, 2010, 22 (1), pp.41-64. ⟨10.1080/10485250903095820⟩ Article dans une revue hal-00120843v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Fitting a Powered Exponential Autocorrelation: Alternatives to Maximum Likelihood via Conjugate Gradient Linear Solvers Didier A. Girard 2022 Autre publication scientifique hal-03701435v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Asymptotic near-efficiency of the “Gibbs-energy and empirical-variance” estimating functions for fitting Matérn models — I: Densely sampled processes Didier A. Girard Statistics and Probability Letters, 2016, 110, pp.191-197. ⟨10.1016/j.spl.2015.12.021⟩ Article dans une revue hal-01955569v1	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		Efficiently estimating some common geostatistical models from «image-type, possibly incomplete» datasets: CGEMEV and its extension to unknown nugget-effect Didier A. Girard , Rémy Drouilhet Spatial Statistics 2019 : Towards Spatial Data Science, Jul 2019, Sitgès, Barcelone, Spain Communication dans un congrès hal-02174478v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		On the excess of average squared error for data-driven bandwidths in nonparametric trend estimation Karim Benhenni , Didier A. Girard , Sana Louhichi Advances in Pure and Applied Mathematics, 2021, 12 (N° Spécial ), pp.15-35. ⟨10.21494/ISTE.OP.2021.0696⟩ Article dans une revue hal-02889802v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More
		On bandwidth selection problems in nonparametric trend estimation under martingale difference errors Karim Benhenni , Didier A. Girard , Sana Louhichi Bernoulli, 2022, 28 (1), pp.395-423. ⟨10.3150/21-BEJ1347⟩ Article dans une revue hal-02514827v2	Envoyer sur ORCID Exporter BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite Export avancé Partager Gmail Facebook X LinkedIn More

Filtrer vos résultats

Three Alternatives to the Likelihood Maximization for Estimating a Centered Matérn (3/2) Process

Estimating a Centered Ornstein-Uhlenbeck Process under Measurement Errors

Estimating a Centered Matérn (1) Process: Three Alternatives to Maximum Likelihood via Conjugate Gradient Linear Solvers

An experimental assessment of the "Gibbs-Energy and Empirical-Variance" estimating equations (via Kalman smoothing) for Matérn processes

Estimators of a Noisy Centered Ornstein-Uhlenbeck Process and Its Noise Variance

Nonparametric Curve Estimation by Smoothing Splines: Unbiased-Risk-Estimate Selector and its Robust Version via Randomized Choices

Nonparametric Density Estimation: Robust Cross-Validation Bandwidth Selection via Randomized Choices

Nonparametric Additive Modeling by Smoothing Splines: Robust Unbiased-Risk-Estimate Selector and a Nonisotropic-Smoothing Improvement

Estimating a centered AR1xAR1 Gaussian field by likelihood maximization or GE-EV matching

Implémentation en R d'une alternative ("CGEM-EV") au maximum de vraisemblance pour des champs de type Matérn

Efficiently estimating some common geostatistical models by ‘energy–variance matching’ or its randomized ‘conditional–mean’ versions

Estimation non-paramétrique de courbes (ou surfaces ou images): vers des régions de confiance pour l'estimateur (localement) L2-optimal

Nonparametric Curve Estimation by Kernel Smoothers under Correlated Errors

Asymptotic near-efficiency of the "Gibbs-energy (GE) and empirical-variance" estimating functions for fitting Matérn models - II: Accounting for measurement errors via "conditional GE mean

Nonparametric Regression and Kernel Smoothing: Confidence Regions for the L2-Optimal Curve Estimate

Nonparametric Curve Estimation by Kernel Smoothers: Efficiency of Unbiased Risk Estimate and GCV Selectors

Estimating the accuracy of (local) cross-validation via randomised GCV choices in kernel or smoothing spline regression

Fitting a Powered Exponential Autocorrelation: Alternatives to Maximum Likelihood via Conjugate Gradient Linear Solvers

Asymptotic near-efficiency of the “Gibbs-energy and empirical-variance” estimating functions for fitting Matérn models — I: Densely sampled processes

Efficiently estimating some common geostatistical models from «image-type, possibly incomplete» datasets: CGEMEV and its extension to unknown nugget-effect

On the excess of average squared error for data-driven bandwidths in nonparametric trend estimation

On bandwidth selection problems in nonparametric trend estimation under martingale difference errors