activity
20212026
most citedFast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models

17 citations · 43 across the 13 of their papers we have counts for

collaborators

13 papers

stat.CO2026

Fast Computation of Nested Cross-Validation for Penalized Regression

Shuyang Cao, Alex Stringer

Cross-validation is a resampling procedure that provides a point estimate of generalization error for any predictive model. Cross-validation is widely used for model selection and…

stat.ME2026

Testing linear combinations of multiple variance components

Alex Stringer, Jeffrey Negrea

We test the hypothesis that simulataneous linear contrasts of multiple variance components equal zero in a Gaussian variance components model via a parametric bootstrap. Applicatio…

astro-ph.GA2025★ 4 cited

Candidate Dark Galaxy-2: Validation and Analysis of an Almost Dark Galaxy in the Perseus Cluster

Dayi Li, Qing Liu, Gwendolyn Eadie +8

Candidate Dark Galaxy-2 (CDG-2) is a potential dark galaxy consisting of four globular clusters (GCs) in the Perseus cluster, first identified in Li et al. (2025) through a sophist…

stat.ME2025

Estimating Associations Between Cumulative Exposure and Health via Generalized Distributed Lag Non-Linear Models using Penalized Splines

Tianyi Pan, Hwashin Hyun Shin, Glen McGee +1

Quantifying associations between short-term exposure to ambient air pollution and health outcomes is an important public health priority. Many studies have investigated the associa…

stat.ME2024★ 2 cited

Case-crossover designs and overdispersion with application in air pollution epidemiology

Samuel Perreault, Gracia Y. Dong, Alex Stringer +2

Over the last three decades, case-crossover designs have found many applications in health sciences, especially in air pollution epidemiology. They are typically used, in combinati…

stat.ME2023

Model-based Smoothing with Integrated Wiener Processes and Overlapping Splines

Ziang Zhang, Alex Stringer, Patrick Brown +1

In many applications that involve the inference of an unknown smooth function, the inference of its derivatives will often be just as important as that of the function itself. To m…

astro-ph.GA2023★ 3 cited

Poisson Cluster Process Models for Detecting Ultra-Diffuse Galaxies

Dayi Li, Alex Stringer, Patrick E. Brown +2

We propose a novel set of Poisson Cluster Process (PCP) models to detect Ultra-Diffuse Galaxies (UDGs), a class of extremely faint, enigmatic galaxies of substantial interest in mo…

math.ST2022★ 3 cited

On the Tightness of the Laplace Approximation for Statistical Inference

Blair Bilodeau, Yanbo Tang, Alex Stringer

Laplace's method is used to approximate intractable integrals in a statistical problems. The relative error rate of the approximation is not worse than . We provide th…

stat.ME2022

Flexible Marginal Models for Dependent Data

Glen McGee, Alex Stringer

Models for dependent data are distinguished by their targets of inference. Marginal models are useful when interest lies in quantifying associations averaged across a population of…

stat.ME2022★ 5 cited

Asymptotics of numerical integration for two-level mixed models

Alex Stringer, Blair Bilodeau, Yanbo Tang

We study mixed models with a single grouping factor, where inference about unknown parameters requires optimizing a marginal likelihood defined by an intractable integral. Low-dime…

stat.ME2021★ 17 cited

Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models

Alex Stringer, Patrick Brown, Jamie Stafford

We define a novel class of additive models, called Extended Latent Gaussian Models, that allow for a wide range of response distributions and flexible relationships between the add…

stat.ME2021★ 3 cited

Stochastic Convergence Rates and Applications of Adaptive Quadrature in Bayesian Inference

Blair Bilodeau, Alex Stringer, Yanbo Tang

We provide the first stochastic convergence rates for a family of adaptive quadrature rules used to normalize the posterior distribution in Bayesian models. Our results apply to th…

stat.CO2021★ 6 cited

Implementing Approximate Bayesian Inference using Adaptive Quadrature: the aghq Package

Alex Stringer

The aghq package for implementing approximate Bayesian inference using adaptive quadrature is introduced. The method and software are described, and use of the package in making ap…