7 papers
Prior elicitation for Bayesian estimation of single-subject connectivity networks
Yiye Jiang, Alice Chevaux, Wendy Meiring +4
Inference of brain functional connectivity networks from resting-state fMRI data is a key focus in neuroimaging. This paper introduces new Bayesian approaches for inferring a funct…
Clustering-Based Inter-Regional Correlation Estimation
Hanâ Lbath, Alexander Petersen, Wendy Meiring +1
A novel non-parametric estimator of the correlation between grouped measurements of a quantity is proposed in the presence of noise. This work is primarily motivated by functional…
Predicting Distributions of Physical Activity Profiles in the NHANES Database Using a Partially Linear Fréchet Single Index Model
Marcos Matabuena, Aritra Ghosal, Wendy Meiring +1
Object-oriented data analysis is a fascinating and evolving field in modern statistical science, with the potential to make significant contributions to biomedical applications. Th…
A Mixed Model Approach for Estimating Regional Functional Connectivity from Voxel-level BOLD Signals
Ruobin Liu, Chao Zhang, Chau Tran +3
Resting-state brain functional connectivity quantifies the synchrony between activity patterns of different brain regions. In functional magnetic resonance imaging, each region com…
Fréchet single index models for object response regression
Aritra Ghosal, Wendy Meiring, Alexander Petersen
With the increasing availability of non-Euclidean data objects, statisticians are faced with the task of developing appropriate statistical methods for their analysis. For regressi…
Analytic tractography: A closed-form solution for estimating local white matter connectivity with diffusion MRI
Matthew Cieslak, Tegan Brennan, Wendy Meiring +5
White matter structures composed of myelinated axons in the living human brain are primarily studied by diffusion-weighted MRI (dMRI). These long-range projections are typically ch…
Spatial prediction variance estimation based on covariance penalty
Roberto Rivera, Wendy Meiring
In practice rarely (if ever) is the spatial covariance known in spatial prediction problems. Often, prediction is performed after estimated spatial covariance parameters are plugge…