Salīdzināt metodes

	Björiešu mikrosimulācija	Aģentu bāzēta mikrosimulācija
Nozare	Simulācija	Simulācija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1990s–2000s	1957 (microsimulation); 2000s (hybrid ABMS)
Autors	Williamson, P.; Birkin, M.; Rees, P. H. and related health-economics researchers	Orcutt, G. H. (microsimulation roots); Bonabeau, E. and others (ABM integration)
Tips	Individual-level probabilistic simulation with Bayesian updating	Hybrid simulation
Pirmavots	Williamson, P., Birkin, M., & Rees, P. H. (2000). The estimation of population microdata by using data from small area statistics and samples of anonymised records. Environment and Planning A, 30(5), 785-816.	Birkin, M., & Clarke, M. (2012). The enhancement of spatial microsimulation models using geodemographics. Annals of Regional Science, 49(2), 515–532.
Citi nosaukumi	Bayesian micro-simulation, BMS, Bayesian individual-level simulation, Probabilistic microsimulation	ABMS, Agent-Based Micro-Simulation, Microsimulation with Agent-Based Modeling, Hybrid ABM-Microsimulation
Saistītās	6	5
Kopsavilkums	Bayesian Microsimulation combines individual-level simulation of heterogeneous populations with Bayesian statistical inference. Each synthetic individual follows a probabilistic life path, while model parameters are governed by prior beliefs updated with observed data. This approach is widely used in health technology assessment, public policy costing, and demographic projection, where uncertainty in both model inputs and structural assumptions must be formally quantified and propagated through to output estimates.	Agent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanisms. It creates virtual populations of heterogeneous agents who evolve over time according to transition probabilities, adaptive behaviors, and social interactions, producing emergent system-level outcomes from micro-level dynamics.