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Limit Theorems in Probability

R. A. Marcus Even though solvents and solvent-solute interactions or interactions with a protein can be very complicated and the resulting motion can be highly anharmonic, under a particular condition there can be a great simplification because of the many coordinates (perhaps analogous to the central-limit theorem in probability theory). [Pg.406]

The mathematics may help us to understand a system that is fundamentally hard to simulate. Examples of this include models involving queues in heavy traffic (Subsection 5.4) or problems in which a very small probability must be estimated. Long simulation runs may be needed to get any accuracy in such situations, whereas various limit theorems in probability theory often give very accurate results. [Pg.2146]

We have seen that a chain has a Gaussian property irrespective of the details of the model employed when the number n of the repeat units is large. This is a typical example of the central limit theorem in probability theory. [Pg.11]


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