Contents 1 Introduction 2 The R program 3 Phenology, an introduction 4 Geo-statistical modelling & analysis of phenological phases 5 Multivariate tools to visualise spatio-temporal patterns in phenology 6 Gaussian Mixture Models of geographical phenomena 7 Analysis of space-time correlations within geographical studies

where f = (f1, . . . , fn) ′ is an unknown vector, σ a positive number and ε1, . . . , εn a sequence of i.i.d. standard Gaussian random variables. For some β ∈ ]0,1[, the aim of this paper is to build a nonasymptotic Euclidean confidence ball for f with probability of coverage 1− β from the observation of Y = (Y1, . . . , Yn) ′. This statistical model includes, as a particular case, the functio...

We review the Bayesian approach to the problem of the elimination of nuisance parameters from a statistical model. Many Bayesian statisticians feel that the framework of Bayesian statistics is so clear and simple that the elimination of nuisance parameters should not be considered a problem: one has simply to compute the marginal posterior distribution of the parameter of interest. However we w...

We present a method for locating salient object features. Salient features are those which have a low probability of being mis-classified with any other feature, and are therefore more easily found in a similar image containing an example of the object. The local image structure can be described by vectors extracted using a standard ‘feature extractor’ at a range of scales. We train statistical...

The goal of voice conversion systems is to modify the voice of a source speaker to be perceived as if it had been uttered by another specific speaker. Many approaches found in the literature work based on statistical models and introduce an oversmoothing in the target features. Our proposal is a new model that combines several techniques used in unit selection for text-tospeech and a non-gaussi...

Quantitative properties of stochastic systems are usually specified in logics that allow one to compare the measure of executions satisfying certain temporal properties with thresholds. The model checking problem for stochastic systems with respect to such logics is typically solved by a numerical approach [31,8,35,22,21,5] that iteratively computes (or approximates) the exact measure of paths ...

The purpose of this paper is to explain the interest and importance of (approximate) models and model selection in Statistics. Starting from the very elementary example of histograms we present a general notion of finite dimensional model for statistical estimation and we explain what type of risk bounds can be expected from the use of one such model. We then give the performance of suitable mo...

We present a statistical method for the motion-based segmentation of deformable structures undergoing non-rigid movements. The proposed approach relies on two models describing the shape of interest, its variability and its movement. The rst model corresponds to a statistical deformable template that constrains the shape and its deformations. The second model is introduced to represent the opti...

Statistical model-checking is a recent technique used for both verification and performance analysis of hybrid systems. It does not suffer from decidability issues or state-space explosion compared to traditional model-checking. Furthermore, it is applicable to more powerful formalisms such as stochastic hybrid automata. Its principle is simple so how simple is it really to make it work in prac...