Page 88 - DCAP601_SIMULATION_AND_MODELING

Simulation and Modelling

Notes

Did u know? The full form of RNG

RNG: Random Number Generator

Table 6.1: Number of Failures in the Crush Battery of Tests (94 tests in total) for
some Standard Normal Random Number Generators

Table 6.2: Number of Failures in the Crush Battery of Tests (94 tests in total) for
Student-t Random Number Generators

6.2 Monte Carlo Computation vs Stochastic Simulation

References to Monte Carlo simulation are often encountered in the and simulation literature.
This somewhat fanciful label refers to a problem-solving methodology that is loosely related
to, but is very different from, the topic that we explore in this textbook. The term refers to a
family of techniques that are used to find solutions to numerical problems. The distinctive
feature of these techniques is that they proceed by constructing an artificial stochastic
(probabilistic) system whose properties contain the solution of the underlying problem. The
origins of the approach can be traced back to Lord Raleigh who used it to develop approximate
solutions to simple partial differential equations. The power of the methodology was exploited
by von Neumann and colleagues in solving complex problems relating to their work in
developing a nuclear arsenal in the latter years of the Second World War. The Monte Carlo label
for the methodology is, in fact, attributed to this group.

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