An EM algorithm for fitting matrix-variate normal distributions on interval-censored and missing data
Sign Up to like & getrecommendations! Published in 2025 at "Statistics and Computing"
DOI: 10.1007/s11222-025-10575-0
Abstract: Matrix-variate distributions are powerful tools for modeling three-way datasets that often arise in longitudinal and multidimensional spatio-temporal studies. However, observations in these datasets can be missing or subject to some detection limits because of the… read more here.
Keywords: censored missing; matrix variate; variate normal; missing data ... See more keywords
Discriminative matrix-variate restricted Boltzmann machine classification model
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DOI: 10.1007/s11276-019-02234-w
Abstract: Matrix-variate Restricted Boltzmann Machine (MVRBM), a variant of Restricted Boltzmann Machine, has demonstrated excellent capacity of modelling matrix variable. However, MVRBM is still an unsupervised generative model, and is usually used to feature extraction or… read more here.
Keywords: classification; restricted boltzmann; matrix variate; model ... See more keywords
Joint Mean and Covariance Estimation with Unreplicated Matrix-Variate Data
Sign Up to like & getrecommendations! Published in 2018 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2018.1429275
Abstract: ABSTRACT 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 to the challenging problem of analyzing… read more here.
Keywords: dependence; covariance estimation; matrix variate; mean covariance ... See more keywords
Matrix-Variate Value-at-Risk: Generalized Beta and F Distributions
Sign Up to like & getrecommendations! Published in 2024 at "American Journal of Mathematical and Management Sciences"
DOI: 10.1080/01966324.2024.2443831
Abstract: Abstract In recent years, there has been a notable increase in the study of matrix-variate distributions and their applications. Significant progress has been made in understanding the properties and statistical inference of these distributions. In… read more here.
Keywords: matrix variate; var; risk; generalized beta ... See more keywords
A graphical model for skewed matrix-variate non-randomly missing data.
Sign Up to like & getrecommendations! Published in 2018 at "Biostatistics"
DOI: 10.1093/biostatistics/kxy056
Abstract: Epidemiological studies on periodontal disease (PD) collect relevant bio-markers, such as the clinical attachment level (CAL) and the probed pocket depth (PPD), at pre-specified tooth sites clustered within a subject's mouth, along with various other… read more here.
Keywords: randomly missing; non randomly; model; matrix variate ... See more keywords
Kernel Regression for Matrix-Variate Gaussian Distributed Signals Over Sample Graphs
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal and Information Processing over Networks"
DOI: 10.1109/tsipn.2022.3202035
Abstract: Recent advances of kernel regression assume that target signals lie over a feature graph such that their values can be predicted with the assistance of the graph learned from training data. In this article, we… read more here.
Keywords: regression; kernel regression; graph; matrix variate ... See more keywords
Entropy Optimization, Maxwell–Boltzmann, and Rayleigh Distributions
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DOI: 10.3390/e23060754
Abstract: In physics, communication theory, engineering, statistics, and other areas, one of the methods of deriving distributions is the optimization of an appropriate measure of entropy under relevant constraints. In this paper, it is shown that… read more here.
Keywords: maxwell boltzmann; optimization; matrix variate; boltzmann rayleigh ... See more keywords
Robust Classification via Finite Mixtures of Matrix Variate Skew-t Distributions
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DOI: 10.3390/math12203260
Abstract: Analysis of matrix variate data is becoming increasingly common in the literature, particularly in the field of clustering and classification. It is well known that real data, including real matrix variate data, often exhibit high… read more here.
Keywords: variate skew; matrix variate; classification; distribution ... See more keywords