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Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

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@SMAC-Group

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lionelvoirol/README.md

Lionel Voirol

Hey !

I am currently a Ph.D. candidate working at the Research Institute for Statistics and Information Science of the University of Geneva advised by Prof. Stéphane Guerrier. Before my Ph.D., I obtained a B.Sc. in Economics and Management and a M.Sc. in Business Analytics at the University of Geneva.

🔭 Research interests

My research interests include:

  • Time series analysis & Signal Processing
  • Boostrap methods
  • Generalized Mixed Linear Models
  • Applied Statistics
  • Computational Statistics
  • Machine Learning
  • High-dimensional Statistics & Variable selection

🔧 Technologies & Tools

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  1. SMAC-Group/gmwmx2 SMAC-Group/gmwmx2 Public

    The gmwmx2 R package implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Voirol, L., Xu, H., Zhang, Y., Insolia, L., Molinari, R. and Guerrier,…

    R 1

  2. SMAC-Group/navigation SMAC-Group/navigation Public

    🛰 The navigation R package implements a framework to analyze the impact of sensor error modeling on performance of integrated navigation (sensor fusion) based on IMU, GPS, and barometer data.

    TeX 5

  3. SMAC-Group/simts SMAC-Group/simts Public

    ⏳ Time Series Tools R package provides a series of tools to simulate, plot, estimate, select and forecast different time series models.

    HTML 15 7

  4. SMAC-Group/course_intro_ds SMAC-Group/course_intro_ds Public

    📊 Source repository for the course: "Introduction to Data Science" given at Unviersity of Geneva

    CSS 1

  5. SMAC-Group/course_data_analytics SMAC-Group/course_data_analytics Public

    💊 Source repository for the website of the class "Modelling and Data Analysis for Pharmaceutical Science" given at Unviersity of Geneva, Spring 2022 and Spring 2023

    HTML 1

  6. demo_array_job_slurm demo_array_job_slurm Public

    Repo to demonstrate how to launch parallelized array job in Slurm

    R 2