ParSet

ParSet is a term used in several disciplines to denote a structured collection of parameters that define a model, device, or experiment. The term is generic and context-dependent, with no single canonical definition that applies across all domains.

A ParSet typically consists of items representing parameters, each with attributes such as name, type (continuous, integer, categorical), and bounds or domain. It may also include a default value, constraints, and metadata describing roles (for example, whether a parameter is a decision variable or a nuisance parameter) and dependencies among parameters. In software, a ParSet is often implemented as a dictionary, object, or specialized data structure that stores both the values and their associated metadata.

In practice, ParSet serves as the defined search or input space for analysis. In optimization and design of experiments, it defines the space from which candidate configurations are sampled. In parameter estimation and calibration, a ParSet stores parameter vectors to be fitted to data. Common operations include sampling within bounds (grid, random, Latin hypercube), validating constraints, and evaluating model outputs to assess performance or fit.

The concept is widely used across fields such as statistics, engineering, and computer simulation. Because it is context-specific, the exact interpretation of a ParSet—its parameters, constraints, and usage—varies between domains and implementations.

See also: parameter space, parameter vector, design of experiments, calibration, sensitivity analysis.