
A central limit theorem for the BenjaminiHochberg false discovery proportion under a factor model
The BenjaminiHochberg (BH) procedure remains widely popular despite hav...
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QuasiNewton QuasiMonte Carlo for variational Bayes
Many machine learning problems optimize an objective that must be measur...
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Designing Experiments Informed by Observational Studies
The increasing availability of passively observed data has yielded a gro...
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Local linear tiebreaker designs
Tiebreaker experimental designs are hybrids of Randomized Control Trial...
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On dropping the first Sobol' point
QuasiMonte Carlo (QMC) points are a substitute for plain Monte Carlo (M...
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Backfitting for large scale crossed random effects regressions
Regression models with crossed random effect error models can be very ex...
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Efficient estimation of the ANOVA mean dimension, with an application to neural net classification
The mean dimension of a black box function of d variables is a convenien...
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A strong law of large numbers for scrambled net integration
This article provides a strong law of large numbers for integration on d...
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Explaining black box decisions by Shapley cohort refinement
We introduce a variable importance measure to explain the importance of ...
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Mean Dimension of Ridge Functions
We consider the mean dimension of some ridge functions of spherical Gaus...
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Unreasonable effectiveness of Monte Carlo
This is a comment on the article "Probabilistic Integration: A Role in S...
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The square root rule for adaptive importance sampling
In adaptive importance sampling, and other contexts, we have unbiased an...
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Optimizing the tiebreaker regression discontinuity design
Motivated by customer loyalty plans, we study tiebreaker designs which ...
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Density estimation by Randomized QuasiMonte Carlo
We consider the problem of estimating the density of a random variable X...
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Propensity Score Methods for Merging Observational and Experimental Datasets
We consider merging information from a randomized controlled trial (RCT)...
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Deterministic parallel analysis
Factor analysis is widely used in many application areas. The first step...
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Importance sampling the union of rare events with an application to power systems analysis
This paper presents a method for estimating the probability μ of a union...
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A randomized Halton algorithm in R
Randomized quasiMonte Carlo (RQMC) sampling can bring orders of magnitu...
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Statistically efficient thinning of a Markov chain sampler
It is common to subsample Markov chain output to reduce the storage burd...
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Moment based estimation of stochastic Kronecker graph parameters
Stochastic Kronecker graphs supply a parsimonious model for large sparse...
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Art B. Owen
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