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	Symulacja wyboru dyskretnego	Mikrosymulacja	Mixed Logit	Symulacja Monte Carlo
Dziedzina	Symulacja	Symulacja	Ekonometria	Podejmowanie decyzji
Rodzina	Process / pipeline	Process / pipeline	Regression model	MCDM
Rok powstania	1974 (McFadden's Nobel-cited logit); simulation extensions throughout 1990s–2000s	1957	2000	1949
Twórca	Daniel McFadden (random utility theory); Kenneth Train (simulation methods)	Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects	Daniel McFadden & Kenneth Train	Metropolis, N., Ulam, S.
Typ	Discrete choice modelling with Monte Carlo simulation	Policy simulation / computational social science	Random-parameters discrete choice model	Robustness wrapper — Monte Carlo uncertainty propagation
Źródło pierwotne	Train, K.E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press.	O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald.	Train, K. E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. ISBN: 978-0-521-74738-7	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Inne nazwy	stated preference simulation, SP simulation, revealed preference modelling, Ayrık Seçim Simülasyonu (Stated Preference / SP Simulation)	Mikrosimülasyon, micro-simulation, policy microsimulation	Random Parameters Logit, Mixed Multinomial Logit, Error Components Logit, Karma Logit Modeli	—
Pokrewne	5	5	3	0
Podsumowanie	Discrete choice simulation is a behavioural modelling method — grounded in random utility theory formalised by Daniel McFadden in the 1970s and extended to simulation-based estimation by Kenneth Train — that estimates how individuals choose among mutually exclusive alternatives and then uses those estimated preference parameters to forecast how choice shares would shift under hypothetical policy or market scenarios. It is the dominant quantitative tool in transport demand analysis, health economics, environmental valuation, and marketing research.	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.	The Mixed Logit model, introduced formally by McFadden and Train (2000) and elaborated in Train (2009), is a flexible discrete choice framework that allows preference parameters to vary randomly across decision-makers. By integrating standard logit probabilities over a mixing distribution of coefficients, it overcomes the restrictive independence of irrelevant alternatives (IIA) property and accommodates unobserved taste heterogeneity, panel data correlation, and complex substitution patterns across alternatives.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.