• Initiatives

    SEMINARS AND SCHOOLS 2018

    ROBUST STATISTICS: FOUNDATIONS AND RECENT DEVELOPMENTS

    April 9-13, 2018
    University of Milano-Bicocca
    Milan, Italy

    Lecturers:
    Anthony Atkinson, London School of Economics, UK
    Marco Riani, University of Parma, IT
    Agustin Mayo-Iscar, University of Valladolid, ES

    RobustStatistics@MilanoBicocca is focused on giving a perspective on the modern challenges of robust statistics, combining novel statistical techniques with challenging problems in different application fields.

    Monday, April 9
    Introduction to robust statistics, Anthony Atkinson (9 a.m.-1 p.m.)
    Applications in Matlab, Marco Riani, Agustin Mayo Iscar  (2.30 – 5.30 p.m.)

    Tuesday, April 10
    Robust regression analysis and transformations,  Anthony Atkinson (9 a.m.-1 p.m.)
    Applications in Matlab, Marco Riani (2.30 – 5.30 p.m.)

    Wednesday, April 11
    Robust multivariate analysis and transformations, Anthony Atkinson (9 a.m.-1 p.m.)
    Applications in Matlab, Marco Riani (2.30 – 5.30 p.m.) 

    Thursday, April 12
    Introduction to robust clustering, Agustin Mayo Iscar (9 a.m.-1 p.m.)
    Applications in R and Matlab, Agustin Mayo Iscar, Marco Riani  (2.30 – 5.30 p.m.) 

    Friday April 13
    Advances in robust clustering, Agustin Mayo Iscar (9 a.m.-1 p.m.)
    Applications in R and Matlab, Agustin Mayo Iscar, Marco Riani  (2.30 – 5.30 p.m.)

    On April 9 and 10 in the morning, lectures will be in Aula Seminari Dismeq (4° floor, room 4026), building U7 and on April 11, 12 and 13 in Aula Seminari demografica (2° floor, room 2062), still in building U7. Lectures in the afternoon will be in Lab904, building U9 (see the map of Milano-Bicocca below).

    The course is open to all people interested in the topic,
    we just ask to send an email to francesca.greselin@unimib.it for organizational matters

    This course is offered by the Department of STATISTICS and QUANTITATIVE METHODS, within:

     

    SEMINARS AND SCHOOLS 2018

    • Applied Bayesian Statistics School (summer school)

    Guido Consonni
    29 August 2016 – 2 September 2016

      • Levy processes

      Laura Ballotta
      15 – 19 February 2016

      • Confidence Distributions

      Nils Lid Hjort
      19 – 22 April 2016

      1. Modern definition and interpretation of confidence distributions
      2. Constructions of confidence distributions
      3. Connections to Bootstrap, Likelihood function, fiducial inference and Bayesian inference
      4. Inference using confidence distributions
      5. Optimality results
      6. Combinations of confidence distributions from different sources of information
      7. Examples and applications to actual data

      Reference book: Hjort, Nils Lid and Tore Schweder (2015). Confidence, Likelihood, Probability. Cambridge University Press

      • Latent Class Models

      Silvia Bacci
      23 – 24 May 2016