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,
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”.
In partnership with the FCT (Fundação para a Ciência a Tecnologia) project, PTDC/MAT-STA/28649/2017. (https://www.maths.ed.ac.uk/~mdecarv/dfus/index.html)
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.
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.
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).