Shape-Constrained Methods: Inference, Applications, and Practice (18w5112)


Hanna Jankowski (York University)

(Colorado State University)

(University of Cambridge)

(Columbia University)


The Banff International Research Station will host the "Shape-Constrained Methods: Inference, Applications, and Practice" workshop from January 28th to February 2nd, 2018.

In reliability engineering, the so-called bathtub curve is a popular way of describing hazard rates because consumer product life cycles often behave that way. The curve goes by the name “bathtub” because it looks like the cross-section of a bathtub: first decreasing, then constant, then increasing again. In statistical models, such an assumption (e.g. increasing, decreasing) is called a shape constraint. Shape-constrained statistical methods have a long history of use in statistics and other fields as practical models of real-world data because they outperform other methods in several key ways. With researchers realizing the advantages of using shape-constrained methods in their work, the field has seen considerable growth in recent years, with both computational and theoretical advances. However, many important theoretical, methodological and computational challenges still remain. The goals of this workshop are to advance the state of knowledge and practice in statistical shape-constrained estimation and to focus future research on the most pressing problems in the field through interaction with researchers in other areas, particularly econometrics, operations research, and machine learning (big data).

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).