Goodness–of–fit tests for regression models: the functional data case

Goodness–of–fit tests for regression models: the functional data caseIn this talk the topic of the goodness–of–fit for regression models with functional covariates is considered. Although several papers have been published in the last two decades for the checking of regression models, the case where the covariates are functional is quite recent and has became of interest in the last years. We will review the very recent advances in this area and we will propose a new goodness–of–fit test for the null hypothesis of a functional linear model with scalar response. Lecturer: Wenceslao González-Manteiga, Univ. de Santiago de Compostela, Spain.

Functional Regression Analysis

Functional Regression AnalysisThe aim of this presentation is to revise the functional regression models with scalar response (Linear, Nonlinear and Semilinear) and the extension to the more general case where the response belongs to the exponential family (binomial, poisson, gamma, ...). This extension allows to develop new functional classification methods based on this regression models. Some examples along with code implementation in R are provided during the talk. Lecturer: Manuel Febrero Bande, Univ. de Santiago de Compostela, Spain.

Advances in the modelling of a system of interacting neurons

How do the membrane potentials of a set of neurons evolve across time? How may we account for influences on these membrane potentials? These questions have been at the core of the scientific agenda of the Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), that is dedicated to integrating mathematical modelling and theoretical neuroscience and is funded by the São Paulo Research Foundation (FAPESP).

Minimum number of edges in a hypergraph guaranteeing a perfect fractional matching and the MMS conjecture

Vladimir Blinovsky

In this paper we prove the Ahlswede-Khachatrian conjecture [1] up to a finite number of cases, which can be checked using modern computers. This conjecture implies the conjecture from [2] and the Manickam-Miklós-Singhi conjecture.

The whole paper is available here.

An introduction to the storage of experimental data in neuroscience

Introdução ao Armazenamento de Dados de Experimentos em Neurociência - Parte 01A set of presentations and background material on strategies to store experimental neuroscientific data, digital questionnaires to collect and store experimental data and meta-data and tools to manage files. Lecturers: Profs. Kelly Braghetto (DCC-IME-USP) and Amanda Nascimento (DC-UFOP).




The Research, Innovation and Dissemination Center for Neuromathematics is hosted by the University of São Paulo and funded by FAPESP (São Paulo Research Foundation).


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