Lecture 10 Outline. Monte Carlo methods History of methods Sequential random number generators Parallel random number generators Generating non-uniform random numbers Monte Carlo case studies. Monte Carlo Methods.
That is, the probability that a random variable will assume a value more than h standard deviations away from its mean is never greater than the square of the reciprocal of h.
Analytical Transformation-probability density function f(x)-cumulative distribution F(x) In theory of probability, a quantile function of a distribution is the inverse of its cumulative distribution function.
Exponential Distribution:An exponential distribution arises naturally when modeling the time between independent events that happen at a constant average rate and are memoryless. One of the few cases where the quartile function is known analytically.
v1 2u1 - 1
v2 2u2- 1
r v12 + v22
until r > 0 and r < 1
f sqrt (-2 ln r /r )
g1 f v1
g2 f v2
This is a consequence of the fact that the chi-square distribution with two degrees of freedom is an easily-generated exponential random variable.
Times Spaces Are Available