Complexity class BPP problems are solved by these methods in polynomial time. Antithetic variates and control variates are common variance reduction techniques for its estimates, while low-discrepancy sequences are used in their "quasi" form. Lazzarini's choice of stopping time and needle lengths when attempting one named for Buffon gave an excessively accurate estimate of pi in just 3,408 tosses. The Gibbs sampler and the more general Metropolis-Hastings algorithm for calculating high-dimensional integrals, and random walk simulation of binomial options pricing models, are examples that make use of Markov chains. For 10 points, name these methods that can be converted into Las Vegas methods by continuing simulation until a sufficiently correct result is produced, named after a city in Monaco.
Complexity class BPP problems are solved by these methods in polynomial time. Antithetic variates and control variates are common variance reduction techniques for its estimates, while low-discrepancy sequences are used in their "quasi" form. Lazzarini's choice of stopping time and needle lengths when attempting one named for Buffon gave an excessively accurate estimate of pi in just 3,408 tosses. The Gibbs sampler and the more general Metropolis-Hastings algorithm for calculating high-dimensional integrals, and random walk simulation of binomial options pricing models, are examples that make use of Markov chains. For 10 points, name these methods that can be converted into Las Vegas methods by continuing simulation until a sufficiently correct result is produced, named after a city in Monaco.
Complexity class BPP problems are solved by these methods in polynomial time.
Monte Carlo methods