Workshop on Astrostatistics

Europe/Rome
Aula Ovest (Osservatorio Astrofisico di Catania)

Aula Ovest

Osservatorio Astrofisico di Catania

Via Santa Sofia 78, 95123, Catania, CT
Marco Montalto (Istituto Nazionale di Astrofisica (INAF))
Description

INAF-OACT is hosting an INAF-wide hybrid Workshop on Astrostatistics during Monday-Wednesday October 7-9, 2024. It will be held in-person at INAF-OACT and will be simultaneously broadcast to all INAF institutes via Zoom.

This workshop is oriented towards graduate students and young researchers who have interests in the principles and practical use of modern statistics for astronomical research. Students attend hybrid lectures and complete Jupyter notebook tutorials in the R statistical software environment associated with the lectures. Slack channels are available for assistance with the tutorials and for astrostatistical consultation on personal research.

Registration is required but there is no cost for the Workshop. It is not an official university course but a certification of participation will be provided.

Participants should expect to be involved with the Workshop full-time during the 3-day course. This includes 5 hours lecture and 2-3 hours individual work on Jupyter tutorials each day. Individual Slack channel research consultation will be available after the Workshop on Thursday October 10. Didactic meterial (slides in pdf and R tutorials in ipynb, html, pdf formats) will be provided during the course.

The instructor, Eric D. Feigelson, Professor of Astronomy & Astrophysics and of Statistics at Penn State University (USA), has been working with statisticians for four decades. He has co-organized Penn State Summer Schools in Statistics for Astronomers, co-organized research conferences Statistical Challenges in Modern Astronomy, was lead author of the graduate textbook Modern Statistical Methods for Astronomy with R Applications, served as inaugural President of IAU Commission on Astroinformatics and Astrostatistics, and is now Statistics Editor for the American Astronomical Society Journals. Andrew Pellegrino, Penn State graduate student, will assist participants with the R Jupyter tutorials.

Participants
  • Adriano Ingallinera
  • Alessandro Vadalà
  • Alex Billi
  • Alexandra Thompson
  • Alfonso Pisapia
  • Alfredo Biagini
  • Ambra Di Piano
  • Ameh James Adah
  • Ameh James Adah
  • Anastasia Tsvetkova
  • Andrea Damonte
  • Antonino Francesco Lanza
  • Antonino Petralia
  • Antonio Trovato
  • Beatrice Eleonora Moreschi
  • Carmelita Carbone
  • Christian Magliano
  • Claudia Di Maio
  • Claudio Arena
  • Daniela Concepción
  • Daniele Fulvio
  • Dario Esposito
  • Davide Abriola
  • Davide Matteo Brustio
  • Dominik Patryk Pacholski
  • Elena Ambrosi
  • Elena Lacchin
  • Elisa Bortolas
  • Elisabetta Carella
  • Ettore Bronzini
  • Eva Sciacca
  • Ezequiel J. Marchesini
  • Fabio Rigamonti
  • Fabrizio Cogato
  • Fabrizio Gentile
  • Federica Santucci
  • Filomena Bufano
  • Francesco Cavallaro
  • Gabriele Galletta
  • Giovanni Bruno
  • Giovanni Della Casa
  • Giulia Mattioli
  • Giuseppe Altavilla
  • giuseppe puglisi
  • Hamza El Byad
  • Ignazio Pillitteri
  • Ilaria Risso
  • Irene Ferranti
  • Javier Alonso Santiago
  • Jesus Maldonado
  • Joaquin Weiss
  • Kazi Rygl
  • Lapo Querci
  • Laura Affer
  • Lin Qiao
  • Loredana Prisinzano
  • Lorenzo Filipello
  • Luca Izzo
  • Marco Laurenti
  • Marco Tarantino
  • Matilde Signorini
  • Matteo Longo Minnolo
  • matteo munari
  • Mauro Orlandini
  • Michela Uslenghi
  • Nino Greco
  • Omima Osman
  • Paola Re Fiorentin
  • Pietro Ferraiuolo
  • ricardo zanmar sanchez
  • Riccardo Ferrazzoli
  • Riccardo Spinelli
  • Ridha Fathima Mohideen Malik
  • Rossella Ragusa
  • saim ali
  • Salvatore Colombo
  • Salvatore Sciortino
  • Sandro Bardelli
  • Sara Zarrinchang
  • Stefano Covino
  • Vidhi Ritesh Tailor
  • Vikash Singh
  • +56
    • 09:30
      Welcome and organization
    • 10:00
      Why astrostatistics? (Intro_Astrostat.pdf)
    • 10:50
      Coffee break
    • 11:10
      Introduction to R (Intro_R.pdf, Tutorial_1_IntroR.R, Tutorial_1_IntroR.ipynb)
    • 14:30
      Nonparametric statistics (Nonpar_stat.pdf)
    • 15:20
      Coffee break
    • 15:40
      Nonparametric density estimation (Nonpar_smooth.pdf, Tutorial_2_Local_regression.R, Tutorial_2_Local_regression.ipynb)
    • 09:30
      Statistical inference and regression (Inference_regression.pdf, Tutorial_3_Regression.R, Tutorial_3_Regression.ipynb)
    • 10:20
      Coffee break
    • 10:40
      Statistical inference and regression (Inference_regression.pdf, Tutorial_3_Regression.R, Tutorial_3_Regression.ipynb)
    • 14:30
      Bayesian inference (Bayesian_infererence.pdf)
    • 15:20
      Coffee break
    • 15:40
      Clustering & classification (Clust_class.pdf)
    • 09:30
      Clustering & classification (Tutorial_4_Clust_class.R, Tutorial_4_Clust_class.ipynb)
    • 10:20
      Coffee break
    • 10:40
      Time series analysis (Time_series.pdf, Tutorial_5_Time_series.R, Tutorial_5_Time_series.ipynb)
    • 14:30
      Research: AutoRegressive Planet Search (AR_planet_search.pdf)
    • 15:20
      Coffee break
    • 15:40
      Best statistical practices for astronomy (Best_stat_practices.pdf)
    • 16:30
      Discussion: Statistical methodology in astronomical research