600 citations · 807 across the 35 of their papers we have counts for
4 papers · 1 filter
Efficient Data Augmentation in Dynamic Models for Binary and Count Data
Jesse Windle, Carlos M. Carvalho, James G. Scott +1
Dynamic linear models with Gaussian observations and Gaussian states lead to closed-form formulas for posterior simulation. However, these closed-form formulas break down when the…
False discovery rate regression: an application to neural synchrony detection in primary visual cortex
James G. Scott, Ryan C. Kelly, Matthew A. Smith +2
Many approaches for multiple testing begin with the assumption that all tests in a given study should be combined into a global false-discovery-rate analysis. But this may be inapp…
Expectation-maximization for logistic regression
James G. Scott, Liang Sun
We present a family of expectation-maximization (EM) algorithms for binary and negative-binomial logistic regression, drawing a sharp connection with the variational-Bayes algorith…
Nonparametric Bayesian testing for monotonicity
James G. Scott, Thomas S. Shively, Stephen G. Walker
This paper studies the problem of testing whether a function is monotone from a nonparametric Bayesian perspective. Two new families of tests are constructed. The first uses constr…