Krahasoni metodat

	Simulimi Monte Karlo Hapësinor	Monte Karlo Sekuencial
Fusha	Statistika bajesiane	Statistika bajesiane
Familja	Bayesian methods	Bayesian methods
Viti i origjinës	1970s–1980s	1993 (particle filter); 2006 (SMC samplers)
Krijuesi	B. D. Ripley and the spatial statistics tradition	Gordon, Salmond & Smith (particle filter); Del Moral, Doucet & Jasra (SMC samplers)
Lloji	computational simulation	Sequential Bayesian computation
Burimi themelues	Ripley, B. D. (1987). Stochastic Simulation. John Wiley & Sons. ISBN: 978-0471818847	Gordon, N. J., Salmond, D. J., & Smith, A. F. M. (1993). Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings F - Radar and Signal Processing, 140(2), 107–113.
Emërtime të tjera	spatial MC simulation, Monte Carlo spatial analysis, stochastic spatial simulation, spatial stochastic simulation	SMC, particle filter, sequential importance resampling, SMC sampler
Të lidhura	4	6
Përmbledhja	Spatial Monte Carlo simulation applies random sampling methods to spatial problems, generating many stochastic realisations of a spatial process — such as a random field, point pattern, or network — to estimate distributional properties, propagate uncertainty, or test spatial hypotheses. It is a cornerstone technique in geostatistics, spatial epidemiology, ecology, and environmental modelling.	Sequential Monte Carlo (SMC) is a family of simulation-based algorithms that approximate evolving probability distributions by propagating and reweighting a cloud of weighted random draws called particles. It handles nonlinear, non-Gaussian models and streams of data naturally, making it the method of choice for real-time state estimation and posterior approximation over complex distributions.