Stochastic modeling relies on a combination of exact solutions and numerical methods. As scientists and engineers tackle more realistic models, the symmetries supporting exact solutions fade. The current chapter sketches a few of the most promising numerical techniques. Further improvements in computing, statistics, and data management are bound to drive the rapidly growing and disorganized discipline of computational probability for decades to come.
KeywordsMarkov Chain Equilibrium Distribution Stochastic Simulation Transition Probability Matrix Renewal Equation
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