66th ISI World Statistics Congress

66th ISI World Statistics Congress

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High-Dimensional and Functional Data Analysis: Modern Methods and Applications

Organiser

D
Sophie Dabo

Participants

  • D
    PROF. DR. Sophie Dabo     (Chair)

  • MC
    Michelle Carey     (Presenter/Speaker)
  • A Nonparametric Penalized Likelihood Approach for Space–Time Point Pattern Density Estimation

  • ID
    Issa-Mbénard DABO     (Presenter/Speaker)
  • High-dimensional analysis of ridge regression for non-identically distributed data with a variance profile

  • GN
    Guy-Martial Nkiet     (Presenter/Speaker)
  • Kernel-based inference for functional data

  • FB
    Prof. Frederic Bertrand     (Presenter/Speaker)
  • Stability-Oriented Variable Selection Across High-Dimensional, Functional and Multi-Block Models

  • SA
    Sena Apeke     (Presenter/Speaker)
  • Wavelet-Enhanced Deep Learning for Multi-Variable Meteorological Time-Series Forecasting in Togo

  • DN
    Dr DrNdèye Niang     (Discussant)

    • Conference

    66th ISI World Statistics Congress

    Category: Bernoulli Society for Mathematical Statistics and Probability (BS)

    Proposal Description

    This session is dedicated to recent methodological and theoretical developments at the interface of mathematical statistics, high dimensional statistics, and Functional Data Analysis (FDA). It seeks to bring together researchers on key topics such as large-scale statistical inference, high-dimensional data modeling, and the analysis of curves, densities, and stochastic processes arising in diverse scientific domains.
    The contributions presented in this session address both foundational and application-driven problems, including parametric, nonparametric estimation in high-dimensional functional data analysis, as well as the incorporation of PDE and machine learning techniques. Particular attention is paid to applications in areas such as environmental sciences, economics, and health.
    This session serves as a forum for exchanges between researchers based in Africa and those working in other regions of the world, with the objective of jointly addressing methodological and practical challenges associated with the analysis of functional, high-dimensional and complex real-world datasets.

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