Results 41 to 50 of about 3,990 (166)
Default Priors in a Zero-Inflated Poisson Distribution: Intrinsic Versus Integral Priors
MathematicsPrior elicitation is an important issue in both subjective and objective Bayesian frameworks, where prior distributions impose certain information on parameters before data are observed.
Junhyeok Hong, Kipum Kim, Seong W. Kim
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Advances in Civil Engineering, 2019 In order to improve the estimation accuracy of bearing capacity of pile foundation, a new forecast method of bearing capacity of pile foundation was proposed on Jeffrey’s noninformative prior using the MCMC (Markov chain Monte Carlo) method of the ...
Zuolong Luo, Fenghui Dong
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Oikos, EarlyView.Partner fidelity is a key component of reproductive strategies in socially monogamous species, yet its adaptive value remains context dependent and poorly understood outside environments with short breeding seasons. In most bird species, partners may remain together or re‐pair between successive nesting attempts, but it remains unclear which components
Kateřina Brynychová +7 more
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The Impact of Prior Information on Bayesian Latent Basis Growth Model Estimation
SAGE Open, 2017 Latent basis growth modeling is a flexible version of the growth curve modeling, in which it allows the basis coefficients of the model to be freely estimated, and thus the optimal growth trajectories can be determined from the observed data.
Dingjing Shi, Xin Tong
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Graph‐Laplacian modeling of spatiotemporal effects for house price estimation
Real Estate Economics, EarlyView.Abstract Many variables involve the modeling of spatial effects, and their dynamics over time. This article presents a linear model in which spatiotemporal random effects are modeled by graph‐Laplacians. A graph‐Laplacian flexibly encodes adjacency in both space and time, in our case not depending on unknown parameters. The graph‐Laplacian can be input
Willem P Sijp, Marc K. Francke
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To vary or not to vary: A flexible empirical Bayes factor for testing variance components
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
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Comparative noninformativities of quantum priors based on monotone metrics [PDF]
Physics Letters A, 1998 7 pages, LaTeX, minor changes, to appear in Physics Letters ...
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On Integral Priors for Multiple Comparison in Bayesian Model Selection
International Statistical Review, EarlyView.Summary Noninformative priors constructed for estimation purposes are usually not appropriate for model selection and testing. The methodology of integral priors was developed to get prior distributions for Bayesian model selection when comparing two models, modifying initial improper reference priors. We propose a generalisation of this methodology to
Diego Salmerón +2 more
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Plant Breeding, EarlyView.ABSTRACT Doubled haploid (DH) technology has been widely adopted in maize (Zea mays L.) breeding programs due to its ability to reduce breeding cycle time and optimize costs. Early ploidy identification is essential for maximizing the efficiency of DH production, particularly prior to chromosome doubling.
Mariana Martins Marcondes +7 more
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Simple Marginally Noninformative Prior Distributions for Covariance Matrices
Bayesian Analysis, 2013 A family of prior distributions for covariance matrices is studied. Members of the family possess the attractive property of all standard deviation and correlation parameters being marginally noninformative for particular hyper-parameter choices. Moreover, the family is quite simple and, for approximate Bayesian inference techniques such as Markov ...
Huang, Alan, Wand, M. P.
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