Abstract:
As a statistical parameter, the mode has been traditionally considered little relevant, at least as compared to its more prominent cousins, the mean and the median. However, a number of statistical problems have recently found an unexpected solution by inspecting them through a 'modal perspective'. These include classical tasks such as clustering or regression. This has led to a renewed interest in estimation and inference for the mode. In this talk we will survey the standard approaches to mode estimation and explore the consequences of applying this modern modal methodology to other, seemingly unrelated, fields.