Results 131 to 140 of about 8,348,933 (325)
Bayesian priors and nuisance parameters
, 2016 Bayesian techniques are widely used to obtain spectral functions from correlators. We suggest a technique to rid the results of nuisance parameters, ie, parameters which are needed for the regularization but cannot be determined from data. We give examples where the method works, including a pion mass extraction with two flavours of staggered quarks at
Gupta, Sourendu, Lahiri, Anirban
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River Research and Applications, EarlyView.ABSTRACT River regulation following damming is often associated with deleterious downstream effects, in large part due to reduced total discharge and disruption of seasonal flooding. These effects would be expected to be exacerbated by drought, particularly extended drought.
Jeffrey G. Holmquist +1 more
wiley +1 more source
Incidental Versus Random Nuisance Parameters
The Annals of Statistics, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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VIEW, EarlyView.Large‐scale cohorts and multimodal biomedical data have enabled powerful predictive models for clinical risk stratification, but prediction alone cannot guide effective interventions. This review introduces causal artificial intelligence as a design‐first framework that integrates target trial emulation, causal discovery, and robust effect estimation ...
Linlin Cao +5 more
wiley +1 more source
Journal of Vinyl and Additive Technology, EarlyView.This study shows that incorporating 5–10 wt.% Posidonia oceanica, with or without micro‐talc, in PBSA preserves thermal stability, modifying crystallization behavior, and maintains good filler dispersion and interfacial adhesion. Mechanical properties are moderately stiffened.
Chiara Pedrotti +8 more
wiley +1 more source
Bayesian inference: more than Bayes’s theorem
Frontiers in Astronomy and Space SciencesBayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
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Wildlife Biology, EarlyView.Second‐order habitat selection is influenced by a variety of factors, including individual‐ and species‐specific traits and resource requirements, as well as landscape characteristics. By comparing home range characteristics across individuals, species, and landscapes, we can draw conclusions regarding whether and how different factors influence home ...
Morgan J. Farmer +4 more
wiley +1 more source
Ontogeny of foraging behaviour in an opportunistic gull inhabiting urban marine ecosystems
Wildlife Biology, EarlyView.Urbanization affects ecosystems by reducing biodiversity and displacing species from native habitats. While some suffer, others, like urban wildlife, adapt through innovative feeding and behaviours that improve their fitness in human‐altered settings. Despite research on wildlife in urban areas, the development of foraging behaviour in urban species is
Joan Navarro +7 more
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New to town: home range size, habitat selection and behavioral adaptations by urban hares
Wildlife Biology, EarlyView.European hares Lepus europaeus have recently been shown to colonize urban areas in different parts of Europe. This appears to be a novel phenomenon, and little is known about the space use and behavioral adaptations of hares living in urban areas. Here, we describe the first findings concerning home range sizes from GPS‐collared hares (n = 3) in Aarhus
Martin Mayer +2 more
wiley +1 more source
European Physical Journal C: Particles and FieldsWe reanalyze the spectral lag data for GRB 160625B using frequentist inference in order to constrain the energy scale $$(E_{QG})$$ ( E QG ) of Lorentz Invariance Violation (LIV).
Shantanu Desai, Shalini Ganguly
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