Parametersett

Parametersett, a Norwegian term meaning parameter set, refers to the collection of parameter values that determine the behavior of a model, system, or process. It represents the domain of plausible values that the parameters may take under specified constraints and conditions.

In mathematics and statistics, a parameter set is the subset of the parameter space that is considered for a given problem. It can define the family of distributions being studied, the range of possible model forms, or the allowable values for estimation. The concept is central to identifiability, estimation, and inference, since the chosen parameter set affects what can be learned from data.

In optimization and simulation, the parameter set defines the feasible region for search and calibration. The parameter vector that is used in a particular run is an element of this set. Constraints—such as bounds, equalities, or inequalities—shape the set and influence solution quality, convergence, and robustness.

In computer science and engineering, a parameter set may include both model parameters (weights, rates) and configuration options (hyperparameters, tolerances). During training or calibration, algorithms search for the most appropriate parameter set given objectives and data. Sensitivity analysis and uncertainty quantification often examine how changes within the parameter set affect outcomes.

Examples include a linear model with parameters a and b, where the parameter set comprises all pairs (a, b) within specified bounds, or a simulation with a broader set of initial conditions and constants.