extremes

Extremes are values or points that lie at the boundary of a defined domain, where a quantity reaches its highest or lowest attainable value within that domain. In mathematics, the terms extrema refer to maxima and minima, which can be further classified as global (absolute) extrema or local (relative) extrema depending on whether the value is the greatest or least across the entire domain or only in a neighborhood.

In calculus and analysis, extrema are often found by identifying critical points where the derivative is zero or undefined, then applying tests such as the second derivative test or changes in monotonicity. Optimization can also involve constraints, solved with methods like Lagrange multipliers or convex optimization when the objective and feasible region satisfy certain properties. The study of extrema is central to many problems in optimization theory, economics, engineering, and physics.

In statistics, the study of extremes focuses on tail behavior and rare events. Extreme value theory seeks limiting distributions for the maxima (or minima) of samples as the sample size grows, leading to three main families: Gumbel, Frechet, and Weibull. Practical approaches include block maxima and peak-over-threshold methods, used in risk assessment for finance, engineering, and environmental science. Extreme analysis often involves considerations of dependence, sample size, and model adequacy to accurately capture rare events.

Real-world examples include extreme weather events, earthquakes, market crashes, and structural loads beyond typical conditions. Because extremes can be sensitive to measurement scales and data, careful data handling, robust estimation, and appropriate modeling choices are essential. Overall, the concept of extremes provides a framework to study boundary behavior across disciplines, from pure mathematics to applied sciences.