activity
20082019
most citedParameters estimation for asymmetric bifurcating autoregressive processes with missing data

26 citations · 61 across the 9 of their papers we have counts for

collaborators

10 papers

stat.ME2019

The revisited knockoffs method for variable selection in L1-penalised regressions

Anne Gégout-Petit, Aurélie Gueudin-Muller, Clémence Karmann

We consider the problem of variable selection in regression models. In particular, we are interested in selecting explanatory covariates linked with the response variable and we wa…

stat.AP2018

A new centered spatio-temporal autologistic regression model. Application to spatio-temporal analysis of esca disease in a vineyard

Anne Gégout-Petit, Lucia Guérin-Dubrana, Shuxian Li

We propose a new centered autologistic spatio-temporal model for binary data on a lattice. The centering allows the interpretation of the autoregression coefficients in separating…

stat.AP2018

Penalized polytomous ordinal logistic regression using cumulative logits. Application to network inference of zero-inflated variables

Aurélie Deveau, Anne Gégout-Petit, Clémence Karmann

We consider the problem of variable selection when the response is ordinal, that is an ordered categorical variable. In particular, we are interested in selecting quantitative expl…

stat.AP2012★ 1 cited

Hidden Markov Model for the detection of a degraded operating mode of optronic equipment

Camille Baysse, Didier Bihannic, Anne Gégout-Petit +2

As part of optimizing the reliability, Thales Optronics now includes systems that examine the state of its equipment. The aim of this paper is to use hidden Markov Model to detect…

math.PR2012

Random coefficients bifurcating autoregressive processes

Benoîte de Saporta, Anne Gégout-Petit, Laurence Marsalle

This paper presents a model of asymmetric bifurcating autoregressive process with random coefficients. We couple this model with a Galton Watson tree to take into account possibly…

math.ST2012★ 1 cited

Nonparametric estimation of the conditional distribution of the inter-jumping times for piecewise-deterministic Markov processes

Romain Azaïs, François Dufour, Anne Gégout-Petit

This paper presents a nonparametric method for estimating the conditional density associated to the jump rate of a piecewise-deterministic Markov process. In our framework, the est…

math.ST2012★ 12 cited

Nonparametric estimation of the jump rate for non-homogeneous marked renewal processes

Romain Azaïs, François Dufour, Anne Gégout-Petit

This paper is devoted to the nonparametric estimation of the jump rate and the cumulative rate for a general class of non-homogeneous marked renewal processes, defined on a separab…

math.ST2011★ 1 cited

Asymmetry tests for Bifurcating Auto-Regressive Processes with missing data

Benoîte de Saporta, Anne Gégout-Petit, Laurence Marsalle

We present symmetry tests for bifurcating autoregressive processes (BAR) when some data are missing. BAR processes typically model cell division data. Each cell can be of one of tw…

math.PR2010★ 26 cited

Parameters estimation for asymmetric bifurcating autoregressive processes with missing data

Benoîte de Saporta, Anne Gégout-Petit, Laurence Marsalle

We estimate the unknown parameters of an asymmetric bifurcating autoregressive process (BAR) when some of the data are missing. In this aim, we model the observed data by a two-typ…

math.ST2008★ 20 cited

Likelihood for generally coarsened observations from multi-state or counting process models

Daniel Commenges, Anne Gégout-Petit

We consider first the mixed discrete-continuous scheme of observation in multistate models; this is a classical pattern in epidemiology because very often clinical status is assess…