[ABE-L] Seminários em Estatística e Ciência de Dados - UFBA

[Paulo C Rodrigues]

Prezados Colegas,

na próxima sexta, dia 26 de abril pelas 11h00, vamos dar continuidade aos
Seminários em Estatística e Ciência de Dados da Universidade Federal da
Bahia. Nesta atividade teremos uma mistura entre seminários online e
seminários presenciais. *Este será Online* (com transmissão no Auditório do
IME/UFBA).

Temos o prazer de anunciar que a palestrante neste seminário é a
*Professora  **Nalini Ravishanker*. A Nalini é Professora e Diretora do
Programa de Graduação da Universidade de Connecticut, nos Estados Unidos. É
também a Co-Editora Chefe do International Statistical Reviw e atual
Presidente da International Society for Business and Industrial Statistics.

A participação neste seminário poderá ser presencial no Auditório do
Instituto de Matemática e Estatística da UFBA ou via YouTube. Mais detalhes
abaixo.

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*Título*: Hierarchical Dynamic Models for Multivariate Times Series of
Counts

*Resumo*:
Discrete-valued time series modeling is emerging as an important area for
many applications, as discussed in the recent CRC Handbook of
Discrete-valued Time Series. Specifically, there is increasing interest in
modeling univariate and multivariate time series of counts responses on
several subjects as a function of subject-specific and/or time-dependent
covariates. This talk presents a Bayesian framework for estimation and
prediction by assuming a multivariate Poisson sampling distribution for the
count responses and by fitting a hierarchical dynamic model which
incorporates the temporal dependence as well as dependence between the
components of the response vector.  We illustrate this on ecology data to
model count responses on different gastropod species. We also discuss a
level correlated model (LCM) which enables us to account for association
among the components of the response vector, possible overdispersion, and
allows us combine different marginal count distributions and to build a
hierarchical model for the vector time series of counts. We discuss the use
of R-INLA for fast implementation of this flexible framework. We illustrate
this on a marketing data set, by modeling the monthly prescription counts
by physicians of a focal drug from a multinational pharmaceutical firm
along with monthly counts of other competing drugs with sizable market
share for the same therapeutic category.

*Data*: 11h00 do dia 26 de abril de 2019

*Local*: Auditório do Instituto de Matemática e Estatística da UFBA

*Transmissão ao vivo online em*: https://youtu.be/M9LJ2cyyTkw
====================================================

Partilhem com os vossos colegas!

São todos bem vindos!

Um abraço,
Paulo Canas Rodrigues
Jalmar Carrasco

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Paulo Canas Rodrigues
*Assistant Professor*, Federal University of Bahia <http://ufba.br>, Brazil
*Research Director*, CAST <https://research.uta.fi/cast/>, University of
Tampere, Finland
*President*, Brazilian Region of the International Biometric Society
<http://www.rbras.org.br>
*Vice-Coordinator*, Specialization in Data Science and Big Data
<http://ecd.ufba.br>
*Past-Chairman*, Latin American Regional Section (LARS) of the IASC
<http://iasc-isi.org>
*Council Member*, International Statistical Institute <https://isi-web.org/>
*Council Member,* International Society for Business and Industrial
Statistics <http://www.isbis-isi.org/>

CV Lattes: http://lattes.cnpq.br/0029960374321970
Web: http://sites.google.com/site/paulocanas/
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