2 citations · 6 across the 13 of their papers we have counts for
15 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…
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…
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…
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…
Better bootstrap t confidence intervals for the mean
Art B. Owen
This article explores combinations of weighted bootstraps, like the Bayesian bootstrap, with the bootstrap method for setting approximate confidence intervals for the mean of a…
On the optimization of discrepancy measures
François Clément, Nathan Kirk, Art B. Owen +1
Numerical optimizations can find point sets with lower discrepancies than prior methods based on algebra, and discrepancies are computationally attractive for this. The …
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…
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…
Optimal Correlation for Bernoulli Trials with Covariates
Tim Morrison, Art B. Owen
Given covariates for units, each of which is to receive a treatment with probability , we study the question of how best to correlate their treatment assignments to minimi…
Coverage errors for Student's t confidence intervals comparable to those in Hall (1988)
Art B. Owen
Table 1 of Hall (1988) contains asymptotic coverage error formulas for some nonparametric approximate 95\% confidence intervals for the mean based on IID samples. The table inc…
Error estimation for quasi-Monte Carlo
Art B. Owen
Quasi-Monte Carlo sampling can attain far better accuracy than plain Monte Carlo sampling. However, with plain Monte Carlo sampling it is much easier to estimate the attained accur…
Constrained Design of a Binary Instrument in a Partially Linear Model
Tim Morrison, Minh Nguyen, Jonathan Chen +2
We study the question of how best to assign an encouragement in a randomized encouragement study. In our setting, units arrive with covariates, receive a nudge toward treatment or…
Skewness of a randomized quasi-Monte Carlo estimate
Zexin Pan, Art B. Owen
Some recent work on confidence intervals for randomized quasi-Monte Carlo (RQMC) sampling found a surprising result: ordinary Student 95% confidence intervals based on a modest…
Biases in estimates of air pollution impacts: the role of omitted variables and measurement errors
Dan M. Kluger, David B. Lobell, Art B. Owen
Observational studies often use linear regression to assess the effect of ambient air pollution on outcomes of interest, such as human health indicators or crop yields. Yet polluti…
Super-polynomial accuracy of one dimensional randomized nets using the median-of-means
Zexin Pan, Art B. Owen
Let be analytic on with for some constant and . We show that the median estimate of under random line…