Florence Chaubert-Pereira

• Researcher at Cirad in Plant Modelling and Statistics
• Lecturer (ATER) at University Montpellier II
• Address:
  • TA A-96/02
  • Avenue Agropolis
  • 34398 Montpellier Cedex 5, France
  • Tel: 33 (0)4 67 61 58 00 (ask for: 54 46) Fax: 33 (0)4 67 61 56 68
  • email:chaubert@cirad.fr

CV in french

CV in english

My thesis work focuses on Markov and semi-Markov switching regression models, i.e. finite mixtures of regression models with (semi-)Markovian dependencies. These statistical models enable to analyse data structured as a succession of stationary phases that are asynchronous between individuals, influenced by time-varying covariates and which present inter-individual heterogeneity. The proposed inference algorithm for (semi-)Markov switching generalized linear models is a gradient EM algorithm. For (semi-)Markov switching linear mixed models, we propose MCEM-like algorithms whose E-step decomposes into two conditional restoration steps: one for the random effects given the state sequences (and the observed data) and one for the state sequences given the random effects (and the observed data). Various conditional restoration steps are presented. We study two types of random effects: individual-wise random effects and environmental random effects. The relevance of these models is illustrated by the analysis of forest tree growth influenced by climatic covariates. These models allow us to identify and characterize the three main growth components (ontogenetic component, environmental component and individual component). We show that the weight of each component varies according to species and silvicultural interventions.

• Latent variable models for time series and longitudinal data,
• Mixed effect models, regression models, dynamical models
• Hidden Markov and semi-Markov models, Markov and semi-Markov switching models
• EM algorithm and extensions (MCEM, gradient EM, . . . )
• MCMC methods

• Analysis of the influence of environmental factors and inter-individual heterogeneity on plant structure and development
• Analysis of shoot elongation and structure,
• Analysis of whole plant structure and development relying on the notion of physiological state,

• Directed and practical work, Introduction to the statistics and the software R, Licence 1 et 2
• Practical work, Linear models, Licence 3
• Practical work, Statistics Applied and data-processing tools, Licence 2
• Course and directed work, Biomathematics, Licence 1
• Pratical work, Biostatistics, Licence 3