Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.
Sign Up to like & getrecommendations! Published in 2017 at "Environmetrics"
DOI: 10.1002/env.2465
Abstract: It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this… read more here.
Keywords: model; model selection; mixture models; spatiotemporal multivariate ... See more keywords
Nonparametric variational learning of multivariate beta mixture models in medical applications
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22506
Abstract: Clustering as an essential technique has matured into a capable solution to address the gap between the growing availability of data and deriving the knowledge from them. In this paper, we propose a novel clustering… read more here.
Keywords: variational learning; medical applications; beta mixture; mixture ... See more keywords
Improving the study of plant evolution with multi-matrix mixture models
Sign Up to like & getrecommendations! Published in 2024 at "Plant Systematics and Evolution"
DOI: 10.1007/s00606-024-01896-0
Abstract: Amino acid substitution model is a key component to study the plant evolution from protein sequences. Although single-matrix amino acid substitution models have been estimated for plants (i.e., Q.plant and NQ.plant), they are not able… read more here.
Keywords: plant evolution; study plant; mixture models; plant ... See more keywords
Development of visual predictive checks accounting for multimodal parameter distributions in mixture models
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Pharmacokinetics and Pharmacodynamics"
DOI: 10.1007/s10928-019-09632-9
Abstract: The assumption of interindividual variability being unimodally distributed in nonlinear mixed effects models does not hold when the population under study displays multimodal parameter distributions. Mixture models allow the identification of parameters characteristic to a… read more here.
Keywords: multimodal parameter; visual predictive; mixture models; parameter distributions ... See more keywords
Bayesian Ensemble Kalman Filter for Gaussian Mixture Models
Sign Up to like & getrecommendations! Published in 2024 at "Mathematical Geosciences"
DOI: 10.1007/s11004-024-10160-7
Abstract: Inverse theory and data assimilation methods are commonly used in earth and environmental science studies to predict unknown variables, such as the physical properties of underground rocks, from a set of measured geophysical data, like… read more here.
Keywords: ensemble kalman; mixture models; kalman filter; mixture ... See more keywords
Deep Gaussian mixture models
Sign Up to like & getrecommendations! Published in 2019 at "Statistics and Computing"
DOI: 10.1007/s11222-017-9793-z
Abstract: Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, deep Gaussian mixture models (DGMM) are introduced and discussed. A DGMM… read more here.
Keywords: mixture; deep gaussian; mixture models; gaussian mixture ... See more keywords
Fast sampling and model selection for Bayesian mixture models
Sign Up to like & getrecommendations! Published in 2025 at "Statistics and Computing"
DOI: 10.1007/s11222-025-10753-0
Abstract: We study Bayesian estimation of mixture models and argue in favor of fitting the marginal posterior distribution over component assignments directly, rather than Gibbs sampling from the joint posterior on components and parameters as is… read more here.
Keywords: model selection; mixture models; mixture; fast sampling ... See more keywords
Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches
Sign Up to like & getrecommendations! Published in 2018 at "Ecological Modelling"
DOI: 10.1016/j.ecolmodel.2018.02.007
Abstract: Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic… read more here.
Keywords: bias; heterogeneity; fitting mixture; count data ... See more keywords
Zero-truncated panel Poisson mixture models: Estimating the impact on tourism benefits in Fukushima Prefecture.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of environmental management"
DOI: 10.1016/j.jenvman.2017.12.082
Abstract: This study proposes an estimation approach to panel count data, truncated at zero, in order to apply a contingent behavior travel cost method to revealed and stated preference data collected via a web-based survey. We… read more here.
Keywords: zero truncated; mixture models; panel; poisson mixture ... See more keywords
Time-for-space substitution in N-mixture models for estimating population trends: a simulation-based evaluation
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-84010-5
Abstract: N-mixture models usually rely on a meta-population design, in which repeated counts of individuals in multiple sampling locations are obtained over time. The time-for-space substitution (TSS) in N-mixture models allows to estimate population abundance and… read more here.
Keywords: time space; mixture models; abundance; mixture ... See more keywords
Continuum shock mixture models for Ni+Al multilayers: Inert mesoscale simulations
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Applied Physics"
DOI: 10.1063/5.0274283
Abstract: Mesoscale modeling of shock waves in Ni+Al multilayers poses significant challenges that are due, in part, to shock-induced chemical reactions. Current modeling approaches utilize reactive molecular dynamics (MD), but they are limited to resolving domains… read more here.
Keywords: shock mixture; inert mesoscale; mixture models; continuum shock ... See more keywords