Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Jean-Yves Brua"'
Publikováno v:
Statistical Topics and Stochastic Models for Dependent Data with Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8653daf6513a7952fae0f90b60004b7
https://doi.org/10.1002/9781119779421.ch7
https://doi.org/10.1002/9781119779421.ch7
Publikováno v:
Sequential Analysis
Sequential Analysis, Taylor & Francis, 2019
Sequential Analysis, Taylor & Francis, 2019
In this paper for the first time the nonparametric autoregression estimation problem for the quadratic risks is considered. To this end we develop a new adaptive sequential model selection method based on the efficient sequential kernel estimators pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be190f2e3fc11d5e6caf25e7968176c5
https://hal.archives-ouvertes.fr/hal-01871165/document
https://hal.archives-ouvertes.fr/hal-01871165/document
Autor:
Jean-Yves Brua
Publikováno v:
Journal of Nonparametric Statistics
Journal of Nonparametric Statistics, American Statistical Association, 2009, 21 (8), pp.991-1002. ⟨10.1080/10485250902993645⟩
Journal of Nonparametric Statistics, American Statistical Association, 2009, 21 (8), pp.991-1002. ⟨10.1080/10485250902993645⟩
This paper deals with the estimation of a regression function at a fixed point in nonparametric heteroscedastic regression models with Gaussian noise. We assume that the variance of the noise depends on the regressor and on the regression function. W
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5823c7c9ccdcf504b15e571c7adce051
https://hal.archives-ouvertes.fr/hal-00192842
https://hal.archives-ouvertes.fr/hal-00192842
Autor:
Jean-Yves Brua
Publikováno v:
Statistical Methodology
Statistical Methodology, Elsevier, 2009, 6 (1), pp.47-60. ⟨10.1016/j.stamet.2008.02.009⟩
Statistical Methodology, Elsevier, 2009, 6 (1), pp.47-60. ⟨10.1016/j.stamet.2008.02.009⟩
International audience; This paper concerns the estimation of the regression function at a given point in nonparametric heteroscedastic models with Gaussian noise or with noise having unknown distribution. In the two cases an asymptotically efficient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efd39002d7bb11ef172c20c5951ad441
Publikováno v:
Sequential Analysis; 2024, Vol. 43 Issue 4, p432-460, 29p
Autor:
Vlad Stefan Barbu, Nicolas Vergne
This book is a collective volume authored by leading scientists in the field of stochastic modelling, associated statistical topics and corresponding applications. The main classes of stochastic processes for dependent data investigated throughout th