Let f:[0,1]^d→ℝ be a completely monotone integrand as defined by
Aistlei...
Crossed random effects structures arise in many scientific contexts. The...
Randomized quasi-Monte Carlo, via certain scramblings of digital nets,
p...
The crossed random-effects model is widely used in applied statistics,
f...
We show that generalized multiquadric radial basis functions (RBFs) on
ℝ...
A model-agnostic variable importance method can be used with arbitrary
p...
We study approximate integration of a function f over [0,1]^s based on
t...
The most popular methods for measuring importance of the variables in a ...
A basic task in explainable AI (XAI) is to identify the most important
f...
In a regression discontinuity design, subjects with a running variable x...
Tie-breaker designs (TBDs), in which subjects with extreme values are
as...
Pre-integration is an extension of conditional Monte Carlo to quasi-Mont...
With climate change threatening agricultural productivity and global foo...
Let f be analytic on [0,1] with |f^(k)(1/2)|≤ Aα^kk! for some
constant A...
The commonly quoted error rates for QMC integration with an infinite low...
We use graphical methods to probe neural nets that classify images. Plot...
When a plain Monte Carlo estimate on n samples has variance σ^2/n,
then ...
The cost of both generalized least squares (GLS) and Gibbs sampling in a...
This paper proposes a uniqueness Shapley measure to compare the extent t...
Cohort Shapley value is a model-free method of variable importance groun...
The Benjamini-Hochberg (BH) procedure remains widely popular despite hav...
Many machine learning problems optimize an objective that must be measur...
The increasing availability of passively observed data has yielded a gro...
Tie-breaker experimental designs are hybrids of Randomized Control Trial...
Quasi-Monte Carlo (QMC) points are a substitute for plain Monte Carlo (M...
Regression models with crossed random effect error models can be very
ex...
The mean dimension of a black box function of d variables is a convenien...
This article provides a strong law of large numbers for integration on
d...
We introduce a variable importance measure to explain the importance of
...
We consider the mean dimension of some ridge functions of spherical Gaus...
This is a comment on the article "Probabilistic Integration: A Role in
S...
In adaptive importance sampling, and other contexts, we have unbiased an...
Motivated by customer loyalty plans, we study tie-breaker designs which ...
We consider the problem of estimating the density of a random variable X...
We consider merging information from a randomized controlled trial (RCT)...
Factor analysis is widely used in many application areas. The first step...
This paper presents a method for estimating the probability μ of a union...
Randomized quasi-Monte Carlo (RQMC) sampling can bring orders of magnitu...
It is common to subsample Markov chain output to reduce the storage burd...
Stochastic Kronecker graphs supply a parsimonious model for large sparse...