• LARS-IASC School on Computational Statistics and Data Science

    Salvador, 15-17 November, 2018

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Welcome to the First LARS-IASC School on Computational Statistics and Data Science

Statistics of extremes: Modeling, inferences, and applications



Salvador, 15-17 November, 2018


About

To increase the development of human capital in computational statistics and support its progress, the Latin American Regional Section of the International Association of Statistical Computing (LARS-IASC) aims to implement a School on Computational Statistics and Data Science (LARS School). The main purpose of the LARS School is to spread the knowledge base and advances in Computational Statistics in the Latin American countries and to increase the number of researchers and data scientists in the field. The main objectives of the LARS School are,

  • To spread the base of knowledge in computational statistics to the Latin American scientific community.
  • To provide an overview of the state-of-the-art of the ongoing research in computational statistics.
  • To provide an overall perspective of the application of computational statistics in data science problems.
  • To present applications where computational statistics have been crucial to solve problems in real-life applications.
  • To increase the number of Latin American researchers and practitioners in computational statistics and data science.


The 1st LARS-IASC School on Computational Statistics and Data Science is organized by the Latin American Regional Section of the International Association for Statistical Computing (LARS-IASC), under the topic “Statistics of extremes: Modeling, inferences, and applications”.


Venue

The 1st LARS-IASC School on Computational Statistics and Data Science will be held at the Ondina Campus of the Federal University of Bahia, Salvador, Brazil, from November 15-17, 2018.


International Organizing Committee

  • Alba Martinez Ruiz (Universidad Católica de la Santísima Concepción, Chile)
  • David F. Muñoz (Instituto Tecnológico Autónomo de México, Mexico)
  • Paulo Canas Rodrigues (Federal University of Bahia, Brazil, and University of Tampere, Finland)

Objetive

This school will offer an overview on modern statistical methods for extreme values, and on how these methods can be used to learn about risk from data. The goal will be on offering preparations for modeling the probability of unlikely but catastrophic events, such as stock market crashes, floods, heatwaves, and alike. Emphasis will be put on recent developments on extensions of standard approaches, including models based on mixtures, methods for nonstationary extremes, and models for tracking the dependence of the extreme values over time. The methods will be illustrated and implemented in R.


Instructors

  • Miguel de Carvalho (University of Edinburgh, UK)
  • Manuele Leonelli (Glasgow University, UK)
  • Dani Gamerman (Universidade Federal do Rio de Janeiro, Brazil)

Registration fees


  • Participants from developing countries: US$ 100.
  • Participants from developed countries: US$ 250.

PAYMENT – Bank Transfer only for Brazilians

Transfer the total amount to the bank account (without expenses for the receiver):
    Bank: Banco do Brasil
    Agency: 3385-5
    Account: 38.676-6
    Account holder: Gilberto Pereira Sassi
    Currency: BRL
    CPF: 229.526.358-11

PAYMENT – only for foreigners




Please send us a scanned copy of the bank transfer by e-mail (pgto.1csds@gmail.com). A confirmation will be sent to you by e-mail after receiving the payment and proof of payment.

The maximum number of participants that we can accept in this LARS-IASC School is 30. The deadline for registration is the 30th of September. The slots will be assigned to the first 30 confirmed registrations (with the payment of registration fee made).




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