63 citations · 351 across the 34 of their papers we have counts for
35 papers
Multi-layered model-based characterisation of the local-Universe galaxy data from the GAMA survey
Fan Dai, Ranjan Maitra, Ivan K. Baldry
Understanding the formation and evolution of galaxy populations requires robust classification and characterisation techniques that jointly account for internal galaxy properties a…
Boxplots and quartile plots for grouped and periodic angular data
Joshua D. Berlinski, Fan Dai, Ranjan Maitra
Angular observations, or observations lying on the unit circle, arise in many disciplines and require special care in their description, analysis, interpretation and visualization.…
Optimized -means color quantization of digital images in machine-based and human perception-based colorspaces
Ranjan Maitra
Color quantization represents an image using a fraction of its original number of colors while only minimally losing its visual quality. The -means algorithm is commonly used in…
Latent characterisation of the complete BATSE gamma ray bursts catalogue using Gaussian mixture of factor analysers and model-estimated overlap-based syncytial clustering
Fan Dai, Ranjan Maitra
Characterising and distinguishing gamma-ray bursts (GRBs) has interested astronomers for many decades. While some authors have found two or three groups of GRBs by analyzing only a…
The envelope of a complex Gaussian random variable
Sattwik Ghosal, Ranjan Maitra
The envelope of an elliptical Gaussian complex vector, or equivalently, the amplitude or norm of a bivariate normal random vector has application in many weather and signal process…
Elliptically-Contoured Tensor-variate Distributions with Application to Improved Image Learning
Carlos Llosa-Vite, Ranjan Maitra
Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate when data comes from distributions with heavier or l…
A Re-defined and Generalized Percent-Overlap-of-Activation Measure for Studies of fMRI Reproducibility and its Use in Identifying Outlier Activation Maps
Ranjan Maitra
Functional Magnetic Resonance Imaging~(fMRI) is a popular non-invasive modality to investigate activation in the human brain. The end result of most fMRI experiments is an activati…
Assessing Certainty of Activation or Inactivation in Test-Retest fMRI Studies
Ranjan Maitra
Functional Magnetic Resonance Imaging~(fMRI) is widely used to study activation in the human brain. In most cases, data are commonly used to construct activation maps corresponding…
Exploratory Factor Analysis of Data on a Sphere
Fan Dai, Karin S. Dorman, Somak Dutta +1
Data on high-dimensional spheres arise frequently in many disciplines either naturally or as a consequence of preliminary processing and can have intricate dependence structure tha…
Fully Three-dimensional Radial Visualization
Yifan Zhu, Fan Dai, Ranjan Maitra
We develop methodology for three-dimensional (3D) radial visualization (RadViz) of multidimensional datasets. The classical two-dimensional (2D) RadViz visualizes multivariate data…
Quantitative Matching of Forensic Evidence Fragments Utilizing 3D Microscopy Analysis of Fracture Surface Replicas
Bishoy Dawood, Carlos Llosa-Vite, Geoffrey Z. Thompson +6
Fractured surfaces carry unique details that can provide an accurate quantitative comparison to support comparative forensic analysis of those fractured surfaces. In this study, a…
Fracture Mechanics-Based Quantitative Matching of Forensic Evidence Fragments
Geoffrey Z. Thompson, Bishoy Dawood, Tianyu Yu +5
Fractured metal fragments with rough and irregular surfaces are often found at crime scenes. Current forensic practice visually inspects the complex jagged trajectory of fractured…
Fast model-based clustering of partial records
Emily M. Goren, Ranjan Maitra
Partially recorded data are frequently encountered in many applications and usually clustered by first removing incomplete cases or features with missing values, or by imputing mis…
Fast matrix-free methods for model-based personalized synthetic MR imaging
Subrata Pal, Somak Dutta, Ranjan Maitra
Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the physical and statist…
A practical model-based segmentation approach for improved activation detection in single-subject functional Magnetic Resonance Imaging studies
Wei-Chen Chen, Ranjan Maitra
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and…
Reduced-Rank Tensor-on-Tensor Regression and Tensor-variate Analysis of Variance
Carlos Llosa-Vite, Ranjan Maitra
Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend t…
An Efficient -modes Algorithm for Clustering Categorical Datasets
Karin S. Dorman, Ranjan Maitra
Mining clusters from data is an important endeavor in many applications. The -means method is a popular, efficient, and distribution-free approach for clustering numerical-value…
CatSIM: A Categorical Image Similarity Metric
Geoffrey Z. Thompson, Ranjan Maitra
We introduce CatSIM, a new similarity metric for binary and multinary two- and three-dimensional images and volumes. CatSIM uses a structural similarity image quality paradigm and…
Estimating Basis Functions in Massive Fields under the Spatial Mixed Effects Model
Karl T. Pazdernik, Ranjan Maitra
Spatial prediction is commonly achieved under the assumption of a Gaussian random field (GRF) by obtaining maximum likelihood estimates of parameters, and then using the kriging eq…
Multi-layered characterization of hot stellar systems with confidence
Souradeep Chattopadhyay, Steven D. Kawaler, Ranjan Maitra
Understanding the physical and evolutionary properties of Hot Stellar Systems (HSS) is a major challenge in astronomy. We studied the dataset on 13456 HSS of Misgeld and Hilker (20…
A Matrix--free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian Data
Fan Dai, Somak Dutta, Ranjan Maitra
This paper proposes a novel profile likelihood method for estimating the covariance parameters in exploratory factor analysis of high-dimensional Gaussian datasets with fewer obser…
Classification with the matrix-variate- distribution
Geoffrey Z. Thompson, Ranjan Maitra, William Q. Meeker +1
Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal…
TiK-means: -means clustering for skewed groups
Nicholas S. Berry, Ranjan Maitra
The -means algorithm is extended to allow for partitioning of skewed groups. Our algorithm is called TiK-Means and contributes a -means type algorithm that assigns observatio…
Visualization of Labeled Mixed-featured Datasets
Yifan Zhu, Fan Dai, Ranjan Maitra
We develop methodology for visualization of labeled mixed-featured datasets. We first investigate datasets with continuous features where our Max-Ratio Projection (MRP) method util…