Comparer des méthodes

	Microsimulation	Quantification de l'incertitude
Domaine	Simulation	Simulation
Famille	Process / pipeline	Process / pipeline
Année d'origine	1957	Seminal modern form: 2002
Auteur d'origine	Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects	Norbert Wiener (polynomial chaos, 1938); extended to Wiener–Askey scheme by Xiu & Karniadakis (2002)
Type	Policy simulation / computational social science	Computational uncertainty analysis framework
Source fondatrice	O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald.	Xiu, D. & Karniadakis, G.E. (2002). The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations. SIAM Journal on Scientific Computing, 24(2), 619–644.
Alias	Mikrosimülasyon, micro-simulation, policy microsimulation	UQ, polynomial chaos expansion, PCE, Kriging surrogate
Apparentées	5	9
Résumé	Microsimulation is a computational method that simulates policy effects by operating directly on a population of individual micro-units — households, firms, patients — and applying rules to each unit according to its own demographic, economic, and behavioural characteristics. Developed conceptually by Guy Orcutt in 1957, it has become the standard tool for evaluating tax reform, pension systems, and health policy before implementation.	Uncertainty Quantification (UQ) is a computational framework for systematically measuring how uncertainty in the inputs of a model propagates into uncertainty in its outputs. Building on Wiener's polynomial chaos theory (1938) and formalised for general stochastic problems by Xiu and Karniadakis (2002), UQ uses two primary strategies: Polynomial Chaos Expansion (PCE), which represents the model output as a series of orthogonal polynomials matched to the input distributions, and Kriging (Gaussian process) surrogates, which replace an expensive simulation with a fast statistical approximation fitted to a small set of carefully chosen runs.