langdistansemodeller
Langdistansemodeller is a term used in Danish-speaking contexts to refer to statistical and computational models that explicitly account for long-range or nonlocal dependencies in data. The central idea is to describe how observations separated by large distances in time, space, or structure may influence each other beyond short-range interactions. The concept is applied across disciplines such as climatology, hydrology, econometrics, linguistics, and network science, wherever long-distance effects are believed to play a role.
Common approaches to langdistansemodeller include methods designed to capture long memory and nonlocal influence. In time
Applications often involve forecasting and inference where effects propagate over extended horizons or distances. Examples include
Evaluation of langdistansemodeller typically relies on out-of-sample predictive performance, information criteria, and diagnostics for long-range dependence,