Random Number Generation
A frequent problem in statistical simulations (the Monte Carlo method) is the generation of pseudo-random numbers that are distributed in a given way. Most algorithms are based on a pseudorandom number generator that produces numbers X that are uniformly distributed in the interval [0,1). These random variates X are then transformed via some algorithm to create a new random variate having the required probability distribution.
Read more about this topic: Probability Distribution
Famous quotes containing the words random, number and/or generation:
“Man always made, and still makes, grotesque blunders in selecting and measuring forces, taken at random from the heap, but he never made a mistake in the value he set on the whole, which he symbolized as unity and worshipped as God. To this day, his attitude towards it has never changed, though science can no longer give to force a name.”
—Henry Brooks Adams (1838–1918)
“One may confidently assert that when thirty thousand men fight a pitched battle against an equal number of troops, there are about twenty thousand on each side with the pox.”
—Voltaire [François Marie Arouet] (1694–1778)
“By this unprincipled facility of changing the state as often, and as much, and in as many ways as there are floating fancies or fashions, the whole chain and continuity of the commonwealth would be broken. No one generation could link with the other. Men would become little better than the flies of a summer.”
—Edmund Burke (1729–1797)