This article explicitly characterizes the distribution of the envelope o...
Statistical analysis of tensor-valued data has largely used the
tensor-v...
Functional Magnetic Resonance Imaging (fMRI) is a popular non-invasive
m...
Functional Magnetic Resonance Imaging (fMRI) is widely used to study
act...
Data on high-dimensional spheres arise frequently in many disciplines ei...
We develop methodology for three-dimensional (3D) radial visualization
(...
Fractured surfaces carry unique details that can provide an accurate
qua...
Fractured metal fragments with rough and irregular surfaces are often fo...
Partially recorded data are frequently encountered in many applications ...
Synthetic Magnetic Resonance (MR) imaging predicts images at new design
...
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in...
Fitting regression models with many multivariate responses and covariate...
Mining clusters from datasets is an important endeavor in many applicati...
We introduce CatSIM, a new similarity metric for binary and multinary tw...
Spatial prediction is commonly achieved under the assumption of a Gaussi...
Hot stellar systems (HSS) are a collection of stars bound together by
gr...
Hot stellar systems (HSS) are a collection of stars bound together by
gr...
This paper proposes a novel profile likelihood method for estimating the...
Matrix-variate distributions can intuitively model the dependence struct...
The K-means algorithm is extended to allow for partitioning of skewed
gr...
This paper develops methodology for 3D radial visualization of
high-dime...
Standard clustering algorithms usually find regular-structured clusters ...
A method to efficiently estimate the bandwidth of the reconstruction fil...
A method to efficiently estimate the bandwidth of the reconstruction fil...
In spatial statistics, a common method for prediction over a Gaussian ra...
The k-means algorithm is the most popular nonparametric clustering metho...
Clustering partitions a dataset such that observations placed together i...
The Ising model is important in statistical modeling and inference in ma...