Results 1 to 10 of about 13,893 (236)
A mixture of SDB skew- t factor analyzers [PDF]
Econometrics and Statistics, 2017 Mixtures of skew-t distributions offer a flexible choice for model-based clustering. A mixture model of this sort can be implemented using a variety of formulations of the skew-t distribution. Herein we develop a mixture of skew-t factor analyzers model for clustering of high-dimensional data using a flexible formulation of the skew-t distribution ...
Paula M. Murray +2 more
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Remote Sensing, 2020 This paper proposes three feature extraction (FE) methods based on density estimation for hyperspectral images (HSIs). The methods are a mixture of factor analyzers (MFA), deep MFA (DMFA), and supervised MFA (SMFA).
Bin Zhao +3 more
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Modelling high-dimensional data by mixtures of factor analyzers [PDF]
Computational Statistics and Data Analysis, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Geoffrey J McLachlan
exaly +6 more sources
Air pollution monitoring: development of ammonia (NH3) dynamic reference gas mixtures at nanomoles per mole levels to improve the lack of traceability of measurements [PDF]
Atmospheric Measurement Techniques, 2022 The measurement of ammonia (NH3) in ambient air is a sensitive and priority topic due to its impact on ecosystems. NH3 emissions have continuously increased over the last century in Europe because of intensive livestock practices and the enhanced use of ...
T. Macé +5 more
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Bayesian Analysis of Mixtures of Factor Analyzers [PDF]
Neural Computation, 2001 For Bayesian inference on the mixture of factor analyzers, natural conjugate priors on the parameters are introduced, and then a Gibbs sampler that generates parameter samples following the posterior is constructed. In addition, a deterministic estimation algorithm is derived by taking modes instead of samples from the conditional posteriors used in ...
Akio Utsugi, Toru Kumagai
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A mixture of generalized hyperbolic factor analyzers [PDF]
Advances in Data Analysis and Classification, 2015 Model-based clustering imposes a finite mixture modelling structure on data for clustering. Finite mixture models assume that the population is a convex combination of a finite number of densities, the distribution within each population is a basic assumption of each particular model.
Cristina Tortora +2 more
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Mixtures of Hidden Truncation Hyperbolic Factor Analyzers [PDF]
Journal of Classification, 2019 The mixture of factor analyzers model was first introduced over 20 years ago and, in the meantime, has been extended to several non-Gaussian analogues. In general, these analogues account for situations with heavy tailed and/or skewed clusters. An approach is introduced that unifies many of these approaches into one very general model: the mixture of ...
Paula M. Murray +2 more
openaire +3 more sources
PLoS ONE, 2020 An important feature of Bayesian statistics is the opportunity to do sequential inference: the posterior distribution obtained after seeing a dataset can be used as prior for a second inference.
Bram Thijssen, Lodewyk F A Wessels
doaj +1 more source
Adaptive Mixtures of Factor Analyzers
CoRR, 2015 Pre-print has 30 pages including the appendix and references. A MATLAB tool of the proposed method is available (see the conclusions section)
Heysem Kaya, Albert Ali Salah
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Robust Cluster Analysis via Mixture Models
Austrian Journal of Statistics, 2016 Finite mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster data sets. In this paper, we focus on the use of normal mixture models to cluster data sets of continuous multivariate data.
Geoffrey J. McLachlan +2 more
doaj +1 more source