149 citations · 167 across the 9 of their papers we have counts for
9 papers
On the universal calibration of heavy-tailed combination tests
Parijat Chakraborty, F. Richard Guo, Kerby Shedden +1
It is often of interest to test a global null hypothesis using multiple, possibly dependent -values by combining their strengths while controlling the type-I error. Recently, se…
Kronecker sum covariance models for spatio-temporal data
Shuheng Zhou, Seyoung Park, Kerby Shedden
In this paper, we study the subgaussian matrix variate model, where we observe the matrix variate data which consists of a signal matrix and a noise matrix . More spec…
Tensor models for linguistics pitch curve data of native speakers of Afrikaans
Michael Hornstein, Shuheng Zhou, Kerby Shedden
We use tensor analysis techniques for high-dimensional data to gain insight into pitch curves, which play an important role in linguistics research. In particular, we propose that…
Non-separable covariance models for spatio-temporal data, with applications to neural encoding analysis
Seyoung Park, Kerby Shedden, Shuheng Zhou
Neural encoding studies explore the relationships between measurements of neural activity and measurements of a behavior that is viewed as a response to that activity. The coupling…
Optimal group testing designs for estimating prevalence with uncertain testing errors
Shih-Hao Huang, Mong-Na Lo Huang, Kerby Shedden +1
We construct optimal designs for group testing experiments where the goal is to estimate the prevalence of a trait by using a test with uncertain sensitivity and specificity. Using…
Joint mean and covariance estimation with unreplicated matrix-variate data
Michael Hornstein, Roger Fan, Kerby Shedden +1
It has been proposed that complex populations, such as those that arise in genomics studies, may exhibit dependencies among observations as well as among variables. This gives rise…