Results 31 to 40 of about 736,978 (266)
POPS: A Software for Prediction of Population Genetic Structure Using Latent Regression Models
The software POPS performs inference of population genetic structure using multilocus genotypic data. Based on a hierarchical Bayesian framework for latent regression models, POPS implements algorithms that improve estimation of individual admixture ...
Flora Jay +3 more
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Torpor is a state of controlled reduction of metabolic rate (M) in endotherms. Assigning measurements of M to torpor or euthermy can be challenging, especially when the difference between euthermic M and torpid M is small, in species defending a high ...
Nicolas J. Fasel +2 more
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Models for the Response of a Mixture
Summary Care needs to be exercised in the choice of model for a mixture system. The polynomial model, for example, cannot satisfactorily account for components which are inert or have additive effects and its coefficients lose their interpretative value when the variables are the proportions of components in the mixture.
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Mixture model averaging for clustering [PDF]
In mixture model-based clustering applications, it is common to fit several models from a family and report clustering results from only the `best' one. In such circumstances, selection of this best model is achieved using a model selection criterion, most often the Bayesian information criterion.
Yuhong Wei, Paul D. McNicholas
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Health Literacy, Self‐Efficacy and Knowledge of Sickle Cell Disease Among Caregivers
ABSTRACT Background Sickle cell disease (SCD) is a hereditary blood disorder in which abnormal haemoglobin leads to severe anaemia, painful crises and organ failure. Caregivers’ health literacy (HL) – their ability to assess, understand and apply information, and interact with healthcare professionals – is crucial for managing children with SCD, yet ...
Melanie Bruinooge +6 more
wiley +1 more source
BAMBI: An R Package for Fitting Bivariate Angular Mixture Models
Statistical analyses of directional or angular data have applications in a variety of fields, such as geology, meteorology and bioinformatics. There is substantial literature on descriptive and inferential techniques for univariate angular data, with the
Saptarshi Chakraborty, Samuel W. K. Wong
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Widely used deep latent variable models (DLVMs), in particular Variational Autoencoders (VAEs), employ overly simplistic priors on the latent space. To achieve strong clustering performance, existing methods that replace the standard normal prior with a Gaussian mixture model (GMM) require defining the number of clusters to be close to the number of ...
Andrew Stirn, David A. Knowles
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On Learning Mixture Models for Permutations [PDF]
In this paper we consider the problem of learning a mixture of permutations, where each component of the mixture is generated by a stochastic process. Learning permutation mixtures arises in practical settings when a set of items is ranked by different sub-populations and the rankings of users in a sub-population tend to agree with each other.
CHIERICHETTI, FLAVIO +3 more
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ABSTRACT Background Pediatric bone sarcoma patients and survivors may experience psychosocial challenges related to childhood cancer after their intensive, body‐altering treatment. This cross‐sectional study aimed to evaluate generic and survivor‐specific psychosocial outcomes in a national cohort of pediatric bone sarcoma patients and survivors, and ...
Hinke van der Hoek +14 more
wiley +1 more source
Uncovering the heterogeneity of a solar flare mechanism with mixture models
The physics of solar flares occurring on the Sun is highly complex and far from fully understood. However, observations show that solar eruptions are associated with the intense kilogauss fields of active regions, where free energies are stored with ...
Bach Viet Do +4 more
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