Results 31 to 40 of about 3,472,659 (303)
Frontiers in Public HealthBackgroundWhether environmentally relevant exposure to volatile organic compounds (VOCs) contributes to frailty remains unknown. We examined urinary VOC metabolites (VOCms) and their mixtures in relation to frailty in a nationally representative U.S ...
Tian-Zhen Qu +4 more
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Frontiers in Psychology, 2018 This simulation study assessed the statistical performance of a skew t mixture latent state-trait (LST) model for the analysis of longitudinal data. The model aims to identify interpretable latent classes with class-specific LST model parameters.
Louisa Hohmann +2 more
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Entropy-Based Anomaly Detection for Gaussian Mixture Modeling
Algorithms, 2023 Gaussian mixture modeling is a generative probabilistic model that assumes that the observed data are generated from a mixture of multiple Gaussian distributions. This mixture model provides a flexible approach to model complex distributions that may not
Luca Scrucca
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The Bayesian Expectation-Maximization-Maximization for the 3PLM
Frontiers in Psychology, 2019 The current study proposes an alternative feasible Bayesian algorithm for the three-parameter logistic model (3PLM) from a mixture-modeling perspective, namely, the Bayesian Expectation-Maximization-Maximization (Bayesian EMM, or BEMM).
Shaoyang Guo +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with sickle cell anemia (SCA) in low‐income settings are at risk of severe malnutrition, but optimal nutritional management has not been established. We evaluated an intensified ready‐to‐use therapeutic food (RUTF) regimen in children with persistent severe malnutrition after initial treatment and assessed whether early ...
Safiya Gambo +9 more
wiley +1 more source
Extensible Gaussian Mixture Model for Image Prior Modeling [PDF]
Jisuanji gongcheng, 2020 To address the inextensible fixed number of components in image prior modeling based on Gaussian Mixture Model(GMM),this paper proposes an extensible GMM model based on Dirichlet Process(DP).Through the addition and merging mechanism of cluster ...
ZHANG Mohua, PENG Jianhua
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Central Nervous System Tumors Among Infants in Canada: A Report From CYP‐C
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Central nervous system (CNS) tumors in infants are rare, pose unique clinical challenges, and lack large‐scale evidence‐based data to guide management. This study seeks to describe CNS tumors in Canadian infants and to compare their outcomes with those of older children.
Samuel Sassine +17 more
wiley +1 more source
Toward a psychological atlas of the world with mixture modeling
, 2016 This article presents findings based on the outcomes of research conducted with 8,883 participants from 33 countries. It employs mixture modeling (latent profile analysis) to classify countries into latent classes. The country-level analyses are based on
Stankov, Lazar, Lee, Jihyun
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Media Statistika, 2020 In the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a ...
Irwan Susanto +1 more
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Mixture-model adaptation for SMT [PDF]
Proceedings of the Second Workshop on Statistical Machine Translation - StatMT '07, 2007 We describe a mixture-model approach to adapting a Statistical Machine Translation System for new domains, using weights that depend on text distances to mixture components. We investigate a number of variants on this approach, including cross-domain versus dynamic adaptation; linear versus loglinear mixtures; language and translation model adaptation;
Foster, George, Kuhn, Roland
openaire +3 more sources