Workshop "Around nonparametric and spatial statistics"

on the September 18, 2019

September 18, 9:30 am
This Workshop is supported partially by the Grenoble Alpes Data Institute and consists of two talks given by Sophie Dabo-Niang from Lille University and Salim Bouzebda from Compiègne University. These two talks will be followed by a PH.D thesis defense of Djihad Benelmadani.

Sophie Dabo-Niang, Université de Lille

Bridging FDA, cell biomechanical phenotype and their biological expressions for Cancer diagnosis


SALLE DE SEMINAIRE 2, RDC du Bât. IMAG.

This work offers a mapping and correlation of different characteristics (biological, physical and genetic) of selected cells lines to model their metastatic potential for improved diagnostic and prognostic capabilities. It aims providing the required tool to predict metastatic potential of a cell by means of physical properties; a method that is faster, cheaper and better suited for point-of-care applications.

For data processing, the needed statistical and computational classification and prediction methods require training with large-scale, heterogeneous, continuous (functional) and spatial datasets including high numbers of cells’ physical and biological properties. A very limited number of models are available for description, visualization, classification and prediction of quantitative data involving continuous (functional) heterogeneous data. Challenges are, in one hand, to use statistical (including functional classification, regression methods) tools able to compute in a non-costly way correlation among huge amounts of data, for training and accuracy prediction. A main issue when analyzing our massive data is to use statistical tools including functional classification, regression methods) able to compute in a non-costly way correlation among huge amounts of data and the ultimate goal of predicting the metastatic potential of cells by physical characterization of cells.

Salim Bouzebda, Université de Compiègne

Empirical processes : Change point and independence tests


SALLE DE SEMINAIRE 2, RDC du Bât IMAG.

In the present talk, we will present some applications of the empirical processes for statistical tests and the nonparametric estimation. We first consider the QQ plot processes to perform statistical tests for change point problems. In the second part, we give applications for testing the independence between random variables (vectors). We finally discuss the copula representation in the regression setting.


Djihad Benelmadani (Thesis defense)

Contribution to nonparametric regression estimation with general autocovariance error process and application to pharmacokinetics


AMPHI 1, Maison JEAN KUNTZMANN.


Fore more details : https://www-ljk.imag.fr/IPS/Event/event180919.html


Published on October 22, 2019

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IMAG Building
Domaine Universitaire de Grenoble