7 papers
Simulation of warping processes with applications to temperature data
Nolwenn Le Méhauté, Jean-François Coeurjolly, Marie-Hélène Descary
Curve registration plays a major role in functional data analysis by separating amplitude and phase variation through warping functions and the accurate simulation of warping proce…
Multivariate Planar Curves: A Statistical Framework for Shape Analysis in Images
Issam-Ali Moindjié, Cédric Beaulac, Marie-Hélène Descary
Recent developments in computer vision have made segmented images widely available across many domains, such as medicine, where segmented radiographs play an important role in diag…
A Functional Approach to Curve Alignment and Shape Analysis
Issam-Ali Moindjié, Cédric Beaulac, Marie-Hélène Descary
In many image analysis problems, the contours of objects carry important statistical information about shape. Such contours are typically affected by deformation variables includin…
Constructing Ancestral Recombination Graphs through Reinforcement Learning
Mélanie Raymond, Marie-Hélène Descary, Cédric Beaulac +1
Over the years, many approaches have been proposed to build ancestral recombination graphs (ARGs), graphs used to represent the genetic relationship between individuals. Among thes…
A convolution type model for the intensity of spatial point processes applied to eye-movement data
Francisco Cuevas-Pacheco, Jean-François Coeurjolly, Marie-Hélène Descary
Estimating the first-order intensity function in point pattern analysis is an important problem, and it has been approached so far from different perspectives: parametrically, semi…
Recovering Covariance from Functional Fragments
Marie-Hélène Descary, Victor M. Panaretos
We consider nonparametric estimation of a covariance function on the unit square, given a sample of discretely observed fragments of functional data. When each sample path is only…
Functional Data Analysis by Matrix Completion
Marie-Hélène Descary, Victor M. Panaretos
Functional data analyses typically proceed by smoothing, followed by functional PCA. This paradigm implicitly assumes that rough variation is due to nuisance noise. Nevertheless, r…