Strong order of convergence refers to the rate at which a numerical method approximates the exact solution of a stochastic differential equation (SDE) in a probabilistic sense. This concept is particularly important when analyzing the performance of numerical methods like the Euler-Maruyama method and higher-order methods for SDEs, as it provides a measure of how closely the numerical solution mimics the true solution as the time step decreases.
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