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hierarchical bayesian linear mixed model  (AgResearch)

 
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    AgResearch hierarchical bayesian linear mixed model
    Hierarchical Bayesian Linear Mixed Model, supplied by AgResearch, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/bayesian+linear+models/hierarchical+bayesian+linear+mixed+model/pm39952750-7-0-50
    Average 90 stars, based on 1 article reviews
    hierarchical bayesian linear mixed model - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    other:

    Article Title: Hierarchical Bayesian linear mixed model to estimate variability in the thermal inactivation parameters for Listeria species.
    Article Snippet: Hierarchical Bayesian linear mixed model to estimate variability in the thermal inactivation parameters for Listeria species Soundarya T. Karamcheti a,b,1 , Gale Brightwell b,c, Phil Bremer a,c, Matthew R. Schofield d,* a Department of Food Science, University of Otago, PO Box 56, Dunedin, 9054, New Zealand b Food System Integrity, AgResearch Ltd., Hopkirk Research Institute, Cnr University Ave and Library Road, Massey University, Palmerston North, 4442, New Zealand c New Zealand Food Safety Science and Research Centre, Massey University, Palmerston North, 4410, New Zealand d Department of Mathematics and Statistics, University of Otago, PO Box 56, Dunedin, 9054, New Zealand A R T I C L E I N F O Keywords: Meta-analysis Thermal inactivation Listeria monocytogenes Uncertainty Variability A B S T R A C T A total of 476 D-values associated with 76 strains of Listeria spp. in liquid media were obtained from 27 scientific articles.



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    Bayesian linear model (beta distribution) of the proportion of prey deliveries given by the female throughout the night (top) and throughout the nestling period (bottom). Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Journal: Ecology and Evolution

    Article Title: Year‐round weather alters nest‐provisioning rates in a migratory owl

    doi: 10.1002/ece3.10333

    Figure Lengend Snippet: Bayesian linear model (beta distribution) of the proportion of prey deliveries given by the female throughout the night (top) and throughout the nestling period (bottom). Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Article Snippet: To assess the effects of precipitation and temperature on owlet growth, we used a Bayesian linear mixed effects model (Gaussian distribution) with a single changepoint, with nestling age as the fixed effect and mass as the response variable.

    Techniques:

    Bayesian linear mixed effects model (gaussian distribution) of adult female (top) and male (bottom) mass (g) throughout the nestling period. Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Journal: Ecology and Evolution

    Article Title: Year‐round weather alters nest‐provisioning rates in a migratory owl

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    Figure Lengend Snippet: Bayesian linear mixed effects model (gaussian distribution) of adult female (top) and male (bottom) mass (g) throughout the nestling period. Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Article Snippet: To assess the effects of precipitation and temperature on owlet growth, we used a Bayesian linear mixed effects model (Gaussian distribution) with a single changepoint, with nestling age as the fixed effect and mass as the response variable.

    Techniques:

    Bayesian changepoint model with random effects (gaussian distribution) of owlet mass (g) throughout the nestling period. Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Journal: Ecology and Evolution

    Article Title: Year‐round weather alters nest‐provisioning rates in a migratory owl

    doi: 10.1002/ece3.10333

    Figure Lengend Snippet: Bayesian changepoint model with random effects (gaussian distribution) of owlet mass (g) throughout the nestling period. Solid and dashed lines represent the fitted value computed using the mean of posteriors, and shaded ribbons represent the 95% credible interval of posteriors. Wet = green/solid, dry = yellow/dashed, warm = red/dashed, cold = blue/solid.

    Article Snippet: To assess the effects of precipitation and temperature on owlet growth, we used a Bayesian linear mixed effects model (Gaussian distribution) with a single changepoint, with nestling age as the fixed effect and mass as the response variable.

    Techniques: