Results 61 to 70 of about 15,712,923 (297)
Geosciences, 2019 Generalized linear models are routinely used in many environment statistics problems such as earthquake magnitudes prediction. Hu et al. proposed Pareto regression with spatial random effects for earthquake magnitudes.
Hou-Cheng Yang, Guanyu Hu, Ming-Hui Chen
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Bayesian Geoadditive Sample Selection Models
Journal of the Royal Statistical Society Series C: Applied Statistics, 2010 SummarySample selection models attempt to correct for non-randomly selected data in a two-model hierarchy where, on the first level, a binary selection equation determines whether a particular observation will be available for the second level, i.e. in the outcome equation.
Wiesenfarth, Manuel, Kneib, Thomas
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On the effect of prior assumptions in Bayesian model averaging with applications to growth regresssion [PDF]
, 2007 We consider the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressor and relatively limited numbers of observations.
Eduardo Ley +4 more
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A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
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BMC Medical Research Methodology, 2010 Background Automatic variable selection methods are usually discouraged in medical research although we believe they might be valuable for studies where subject matter knowledge is limited.
Steineck Gunnar +3 more
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Global Rather Than Vertical‐Selective Saccadic Abnormalities in Progressive Supranuclear Palsy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To test whether vertical saccades are preferentially affected in Progressive Supranuclear Palsy (PSP). Methods PSP patients (n = 24) were compared to age‐matched controls (n = 94) and two degenerative groups (Alzheimer's disease, n = 20; Lewy body disease, n = 50).
Duy Duan Nguyen +6 more
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Yantu gongcheng xuebao, 2023 In order to establish an optimal model for estimating the uniaxial compressive strength (UCS) of rocks as well as its reasonable estimation, a fully Bayesian Gaussian process regression method (fB-GPR) is proposed by combining the Gaussian process ...
SONG Chao , ZHAO Tengyuan , XU Ling
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Post hoc Bayesian model selection
NeuroImage, 2011 This note describes a Bayesian model selection or optimization procedure for post hoc inferences about reduced versions of a full model. The scheme provides the evidence (marginal likelihood) for any reduced model as a function of the posterior density over the parameters of the full model.
Karl J. Friston, Will D. Penny
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Choroid plexus volume (CPV) has been proposed as a neuro‐immunological marker of multiple sclerosis (MS), but its relevance in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD) remains uncertain. We analyzed CPV in 43 individuals with MOGAD, 48 with MS, and 44 healthy controls using a Bayesian Gaussian mixture modeling ...
Jae‐Won Hyun +4 more
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Bayesian Analysis of Sample Selection and Endogenous Switching Regression Models with Random Coefficients Via MCMC Methods [PDF]
, 2002 This paper develops a Bayesian method for estimating and testing the parameters of the endogenous switching regression model and sample selection models.
Odejar, M. A. E.
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