125 citations · 185 across the 9 of their papers we have counts for
6 papers · 1 filter
Bayesian Tensor Regression for Neuroimaging Data
Zahra Naji, Montserrat Fuentes, Liangsuo Ma +1
Multidimensional array data, or tensors, arise naturally in neuroimaging and other high-dimensional applications. We propose a parsimonious Bayesian tensor regression model for stu…
Covariance Kernels on Unordered Pair Spaces: Theory and Applications to Network-Valued Data
Montserrat Fuentes
Many scientific problems are relational: the quantity of interest is a connection between two objects, while information about similarity is available for the objects themselves. W…
From Kriging to Spatial AI: Fifty Years of Spatial Statistics for Complex Dependent Data
Montserrat Fuentes, Veronica B. Patterson
Spatial statistics has grown from kriging for spatial prediction into a broad framework for learning from complex dependent data. This article traces that development from random f…
Smooth Density Spatial Quantile Regression
Halley Brantley, Montserrat Fuentes, Joseph Guinness +1
We derive the properties and demonstrate the desirability of a model-based method for estimating the spatially-varying effects of covariates on the quantile function. By modeling t…
New Parsimonious Multivariate Spatial Model: Spatial Envelope
Hossein Moradi Rekabdarkolaee, Qin Wang, Zahra Naji +1
Dimension reduction provides a useful tool for analyzing high dimensional data. The recently developed \textit{Envelope} method is a parsimonious version of the classical multivari…
Bayesian Spectral Modeling of Microscale Spatial Distributions in a Multivariate Soil Matrix
Maria A. Terres, Montserrat Fuentes, Dean Hesterberg +1
Recent technological advances have enabled researchers in a variety of fields to collect accurately geocoded data for several variables simultaneously. In many cases it may be most…