GUÉDON , Yann

This paper addresses the retrospective or off-line multiple change-point detection problem. In this context, there is a need of efficient diagnostic tools that enable to localize the segmentation uncertainty along the observed sequence. Concerning the segmentation uncertainty, the focus was mainly on the change-point position uncertainty. We...

Models that combine Markovian states with implicit geometric state occupancy distributions and semi-Markovian states with explicit state occupancy distributions, are investigated. This type of model retains the flexibility of hidden semi-Markov chains for the modeling of short or medium size homogeneous zones along sequences but also enables...

This paper addresses the retrospective or off-line multiple change-point detection problem. Methods for exploring the space of possible segmentations of a sequence for a fixed number of change points may be divided into two categories: (i) enumeration of segmentations, (ii) summary of the possible segmentations in change-point or segment...

With regard to multiple change-point models, much effort has been devoted to the selection of the number of change points. But, the proposed approaches are either dedicated to specific segment models or give unsatisfactory results for short or medium length sequences. We propose to apply the slope heuristic, a recently proposed non-asymptotic...

With regard to the retrospective multiple change-point detection problem, much effort has been devoted in recent years to the selection of the number of change points. But, the proposed approaches are either dedicated to specific models (e.g. Gaussian change in the mean model) or give unsatisfactory results for short or medium length sequences....

no abstract

Le problème de détection a posteriori de ruptures multiples est étudié.En ce qui concerne l'incertitude sur la segmentation, les travaux se sont focalisés jusqu'à présent sur l'incertitude concernant la position des ruptures. Nous proposons de poser ce problème d'une façon différente en voyant les modèles de détection de ruptures multiples...

This paper addresses the retrospective or off-line multiple change-point detection problem. Multiple change-point models are here viewed as latent structure models and the focus is on inference concerning the latent segmentation space. Methods for exploring the space of possible segmentations of a sequence for a fixed number of change points...

The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categories: (i) enumeration of state sequences; (ii) summary of the possible state sequences in state profiles; (iii) computation of a global measure of the state sequence...

Over the last 40 years, perceptible advances in dates of flowering stages have been observed in apple and pear trees growing in three cropping areas in France and one in Switzerland. The time-course variation of dates of flowering stages was established for eight chronological sequences. Our aim was to propose a statistical modelling framework...

This report addresses state inference for hidden Markov models. These models rely on unobserved states, which often have a meaningful interpretation. This makes it necessary to develop diagnostic tools for quantification of state uncertainty. The entropy of the state sequence that explains an observed sequence for a given hidden Markov chain...

This paper addresses state inference for hidden Markov models. These models rely on unobserved states, which often have a meaningful interpretation. This makes it necessary to develop diagnostic tools for quantification of state uncertainty. The entropy of the state sequence that explains an observed sequence for a given hidden Markov chain...

Nous introduisons les modèles de Markov cachés graphiques, qui généralisent les chaînes et arbres de Markov cachés (CMCs et AMCs). Nous montrons comment l'incertitude globale sur le processus d'état caché peut être décomposée en une somme d'entropies conditionnelles, qui s'interprètent comme une contribution locale à l'incertitude globale. Nous...

This paper addresses the identification and characterization of developmental patterns in the whole structure of a sympodial species, the apple tree. Dedicated stochastic models (hidden variable-order Markov chains) were used to (i) categorise growth units (GUs) on the basis of their morphological characteristics (number of nodes and...

Abstract. A family of graphical hidden Markov models that generalizes hidden Markov chain (HMC) and tree (HMT) models is introduced. It is shown that global uncertainty on the state process can be decomposed as a sum of conditional entropies that are interpreted as local contributions to global uncertainty. An efficient algorithm is derived to...

Over the last 40 years, perceptible advances in dates of flowering stages have been observed in apple and pear trees growing in three cropping areas in France and one in Switzerland. The time-course variation of dates of flowering stages was established for eight chronological sequences. Our aim was to propose a statistical modelling framework...