10 citations · 15 across the 13 of their papers we have counts for
13 papers
Hypergraph Variable Selection with False Discovery Rate Control
Sarah Organ, Toby Kenney, Hong Gu
Variable selection methods that control the false discovery rate often lose power when predictors exhibit complex dependence structures. We previously showed that selecting hierarc…
Factor State Space Modelling of the Ornstein-Uhlenbeck Process with Measurement Error and its Application
Shanglun Li, Toby Kenney, Hong Gu
Standard Ornstein-Uhlenbeck (OU) models often yield biased parameter estimates when measurement error is ignored. While the Ornstein-Uhlenbeck State Space Model (OUSSM) addresses t…
Setwise Hierarchical Variable Selection and the Generalized Linear Step-Up Procedure for False Discovery Rate Control
Sarah Organ, Toby Kenney, Hong Gu
Controlling the false discovery rate (FDR) in variable selection becomes challenging when predictors are correlated, as existing methods often exclude all members of correlated gro…
Detection of evolutionary shifts in variance under an Ornsten-Uhlenbeck model
Wensha Zhang, Lam Si Tung Ho, Toby Kenney
Sudden changes in environmental conditions can lead to evolutionary shifts not only in the optimal trait value, but also in the diffusion variance under the Ornstein-Uhlenbeck (OU)…
Rank Selection for Non-negative Matrix Factorization
Yun Cai, Hong Gu, Toby Kenney
Non-Negative Matrix Factorization (NMF) is a widely used dimension reduction method that factorizes a non-negative data matrix into two lower dimensional non-negative matrices: One…
Evolutionary shift detection with ensemble variable selection
Wensha Zhang, Toby Kenney, Lam Si Tung Ho
1. Abrupt environmental changes can lead to evolutionary shifts in trait evolution. Identifying these shifts is an important step in understanding the evolutionary history of pheno…
Stone Duality for Topological Convexity Spaces
Toby Kenney
A convexity space is a set X with a chosen family of subsets (called convex subsets) that is closed under arbitrary intersections and directed unions. There is a lot of interest in…
Deconvolution density estimation with penalised MLE
Yun Cai, Hong Gu, Toby Kenney
Deconvolution is the important problem of estimating the distribution of a quantity of interest from a sample with additive measurement error. Nearly all methods in the literature…
SuRF: a New Method for Sparse Variable Selection, with Application in Microbiome Data Analysis
Lihui Liu, Hong Gu, Johan Van Limbergen +1
In this paper, we present a new variable selection method for regression and classification purposes. Our method, called Subsampling Ranking Forward selection (SuRF), is based on L…
Consistency of Ranking Estimators
Toby Kenney
The ranking problem is to order a collection of units by some unobserved parameter, based on observations from the associated distribution. This problem arises naturally in a numbe…
Poisson PCA: Poisson Measurement Error corrected PCA, with Application to Microbiome Data
Toby Kenney, Tianshu Huang, Hong Gu
In this paper, we study the problem of computing a Principal Component Analysis of data affected by Poisson noise. We assume samples are drawn from independent Poisson distribution…
Prior Distributions for Ranking Problems
Toby Kenney, Hao He, Hong Gu
The ranking problem is to order a collection of units by some unobserved parameter, based on observations from the associated distribution. This problem arises naturally in a numbe…
The Adequate Bootstrap
Toby Kenney, Hong Gu
There is a fundamental disconnect between what is tested in a model adequacy test, and what we would like to test. The usual approach is to test the null hypothesis "Model M is the…