13 papers
Randomized quasi-Monte Carlo integration
Art B. Owen
Quasi-Monte Carlo sampling is a numerical integration method that uses points with a space-filling property in designed to give better estimates than plain Monte Carlo me…
Walk on spheres and Array-RQMC
Valerie N. P. Ho, Art B. Owen
We use Array-RQMC sampling in a walk on spheres (WoS) algorithm for Dirichlet boundary value problems. On a collection of problems, we find that Array-RQMC-WoS reduces the Monte Ca…
Randomized quasi-Monte Carlo for walk on spheres
Valerie N. P. Ho, Art B. Owen
We investigate the use of randomized quasi-Monte Carlo (RQMC) in walk on spheres algorithms to solve boundary value problems for functions with Dirichlet boundary conditions in $\m…
Empirical Bernstein and betting confidence intervals for randomized quasi-Monte Carlo
Aadit Jain, Fred J. Hickernell, Art B. Owen +1
Randomized quasi-Monte Carlo (RQMC) methods estimate the mean of a random variable by sampling an integrand at equidistributed points. For scrambled digital nets, the resulting…
Quasi-Monte Carlo with one categorical variable
Valerie N. P. Ho, Art B. Owen, Zexin Pan
We study randomized quasi-Monte Carlo (RQMC) estimation of a multivariate integral where one of the variables takes only a finite number of values. This problem arises when the var…
Zero variance self-normalized importance sampling via estimating equations
Art B. Owen
In ordinary importance sampling with a nonnegative integrand there exists an importance sampling strategy with zero variance. Practical sampling strategies are often based on appro…