Kullback-Leibler information and statistical modeling (2022)

prof. G. Soffritti - Date soggette a variazione

  • Date:

    18 FEBRUARY
    -
    11 MARCH 2022
     from 11:00 to 13:00

  • Event location: Aula IV, Via Belle Arti 41 and STAT PhD Classes Virtual Room

  • Type: Cycle 37 - Mandatory Courses

Lessons schedule

Short Program

  • Statistical models. Model identification and (mis)specification.
  • Kullback-Leibler information, expected log-likelihood and their estimators.
  • Kullback-Leibler information as a criterion for evaluating statistical models that approximate the true distribution of the data.
  • Asymptotic properties of the maximum likelihood estimator in the presence of model misspecification.

 

References:

  • Konishi S. and Kitagawa G. (2008). “Information criteria and statistical modeling”. Springer, New York (Chapter 3).
  • White H. (1982). “Maximum likelihood estimation of misspecified models”. Econometrica, Vol. 50, No. 1. (Jan. 1982), pp. 1-25.