Bruno Portier

发表

Strong uniform consistency and asymptotic normality of a kernel based error density estimator in functional autoregressive models

N. Hilgert, Bruno Portier, 2009, 0905.2327.

On the asymptotic behavior of the Durbin–Watson statistic for ARX processes in adaptive tracking

B. Bercu, Bruno Portier, Victor Vazquez, 2012, 1204.4677.

Partial and Recombined Estimators for Nonlinear Additive Models

Jean-Michel Poggi, Nathalie Chèze, Bruno Portier, 2003 .

A Test of Linearity for Functional Autoregressive Models

Jean-Michel Poggi, Bruno Portier, Jean-Michel Poggi, 1996 .

Mixture of experts for sequential PM10 forecasting in Normandy (France)

Jean-Michel Poggi, Bruno Portier, Benjamin Auder, 2015 .

Spatial outlier detection in the air quality monitoring network of Normandy (France)

Jean-Michel Poggi, Bruno Portier, M. Misiti, 2014 .

Estimation and test of linearity for a class of additive nonlinear models

Jean-Michel Poggi, Bruno Portier, Nathalie Cheze-payaud, 1998 .

Spatial correction of low‐cost sensors observations for fusion of air quality measurements

Jean-Michel Poggi, Bruno Portier, M. Bobbia, 2022, Applied Stochastic Models in Business and Industry.

Revisiting the estimation of the error density in functional autoregressive models

N. Hilgert, Bruno Portier, 2015 .

Adaptive control of parametric nonlinear autoregressive models via a new martingale approach

Bernard Bercu, Bruno Portier, B. Bercu, 2002, IEEE Trans. Autom. Control..

An efficient Averaged Stochastic Gauss-Newton algorithm for estimating parameters of non linear regressions models

P. C'enac, Bruno Portier, Antoine Godichon-Baggioni, 2020, 2006.12920.

Mixture of linear regression models for short term PM10 forecasting in Haute Normandie (France)

Jean-Michel Poggi, Michel Misiti, Yves Misiti, 2015 .

PM10 forecasting using clusterwise regression

Jean-Michel Poggi, Bruno Portier, Jean-Michel Poggi, 2011 .

Strong uniform consistency and asymptotic normality of a kernel based error density estimator in functional autoregressive models

N. Hilgert, Bruno Portier, 2012, Statistical Inference for Stochastic Processes.

Kernel density estimation in adaptive tracking

Bernard Bercu, Bruno Portier, B. Bercu, 2008, 2008 47th IEEE Conference on Decision and Control.

Kernel Density Estimation and Goodness-of-Fit Test in Adaptive Tracking

Bernard Bercu, Bruno Portier, B. Bercu, 2008, SIAM J. Control. Optim..

An Efficient Stochastic Newton Algorithm for Parameter Estimation in Logistic Regressions

Bernard Bercu, Bruno Portier, Antoine Godichon, 2019, SIAM J. Control. Optim..

A New Spherical Mixture Model for Head Detection in Depth Images

Bruno Portier, Denis Brazey, Bruno Portier, 2014, SIAM J. Imaging Sci..

Three Non-Linear Statistical Methods for Analyzing PM10 Pollution in Rouen Area

Jean-Michel Poggi, Bruno Portier, François-Xavier Jollois, 2014 .

Analyse Statistique de la Pollution par les PM10 en Haute-Normandie

Jean-Michel Poggi, Bruno Portier, François-Xavier Jollois, 2009 .

Sequential aggregation of heterogeneous experts for PM10 forecasting

Jean-Michel Poggi, Benjamin Auder, Michel Bobbia, 2016 .

Quantifying local and background contributions to PM10 concentrations in Haute‐Normandie, using random forests

Jean-Michel Poggi, Bruno Portier, François-Xavier Jollois, 2011 .