Exact(1)
Model fit in the Bayesian context relates to assessing the predictive accuracy of a model, and is referred to as posterior predictive checking (Gelman et al., 2004).
Similar(59)
To examine both the impacts of bias and scale in accuracy assessment, we assessed the predictive accuracy of GNN maps in western and southern Oregon.
RMSPE is one of many measures that can be used to assess the predictive accuracy of the various models.
The database is utilized to assess the predictive accuracy of significant existing design recommendations, with respect to the vertical load capacity of the tested beams.
We assessed the predictive accuracy of the STOP-Bang questionnaire in relation to OSA detected by nocturnal oximetry, and postoperative outcomes, in a population undergoing cardiac surgery.
In this report, the total and local-fragment 3D N-linear Algebraic indices [25, 26] (also known as QuBiLS-MIDAS) are employed to assess the predictive accuracy of this approach in QSAR studies.
The authors of the previous paper used data from variable radius plots near northern spotted owl nest sites to assess the predictive accuracy of gradient nearest neighbor (GNN) maps in portions of Oregon and Washington, USA.
In this paper, we empirically assess the predictive accuracy of a large group of models that are specified using principle components and other shrinkage techniques, including Bayesian model averaging and various bagging, boosting, least angle regression and related methods.
The PRELUDE (PRogrammed ELectrical stimUlation preDictive valuE) prospective registry was designed to assess the predictive accuracy of sustained ventricular tachycardia/ventricular fibrillation (VTs/VF) inducibility and to identify additional predictors of arrhythmic events in Brugada syndrome patients without history of VT/VF.
An important feature of this methodology is that it can be used to assess the predictive accuracy of a model even if the model itself is not provided to the evaluator, so that proprietary tools can be evaluated while protecting the developer's intellectual property.
The cohort was then split randomly into two samples of equal size using the first as the sample to develop the risk score, and the second as the test sample to assess the predictive accuracy of the score [23], [24].
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