8 citations · 9 across the 6 of their papers we have counts for
4 papers · 1 filter
An efficient Averaged Stochastic Gauss-Newton algorithm for estimating parameters of non linear regressions models
Peggy Cénac, Antoine Godichon-Baggioni, Bruno Portier
Non linear regression models are a standard tool for modeling real phenomena, with several applications in machine learning, ecology, econometry... Estimating the parameters of the…
An efficient stochastic Newton algorithm for parameter estimation in logistic regressions
Bernard Bercu, Antoine Godichon-Baggioni, Bruno Portier
Logistic regression is a well-known statistical model which is commonly used in the situation where the output is a binary random variable. It has a wide range of applications incl…
An averaged projected Robbins-Monro algorithm for estimating the parameters of a truncated spherical distribution
Antoine Godichon-Baggioni, Bruno Portier
The objective of this work is to propose a new algorithm to fit a sphere on a noisy 3D point cloud distributed around a complete or a truncated sphere. More precisely, we introduce…
On the asymptotic behavior of the Durbin-Watson statistic for ARX processes in adaptive tracking
Bernard Bercu, Bruno Portier, Victor Vazquez
A wide literature is available on the asymptotic behavior of the Durbin-Watson statistic for autoregressive models. However, it is impossible to find results on the Durbin-Watson s…