Robustness Theory and Methodology: Recent Advances and Future Directions (16w2693)


(University of Alberta)

(University of Victoria)


The Banff International Research Station will host the "Robustness theory and methodology: recent advances and future directions" workshop in Banff from September 2 to September 4, 2016

Data are continuously generated and collected on a massive scale using experiments, surveys, online records, and a variety of other methods and often contain unusual observations (outliers) due to failed experiments, recording errors or other causes. It is well known that robust statistical procedures can successfully detect outliers and provide reliable inferences, especially for multi-dimensional data. On the other hand, non-robust methods are highly influenced by outliers, so they are not as reliable.
Robust method constructs the optimal experimental design when there are possible deviations from model assumptions. The resulting designs are highly efficient and robust against minor model departures, and may make them flexible to use in real applications. There are many applications in various research fields where experiments are performed to develop new theories and/or improve the quality of processes and services, for example, experiments are done to investigate manufacturing processes, climate change, and drug developments.
This workshop will showcase important advances in robust estimation, robust design, and numerical methods developed in the last three decades. As we face many challenges building robust methods for analyzing big and high dimensional data, future anticipated research areas will be discussed.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).