Results 71 to 80 of about 164,931 (293)
Bayesian statistics in oncology: a guide for the clinical investigator [PDF]
, 2009 The rise of evidence-based medicine as well as important progress in statistical methods and computational power have led to a second birth of the >200-year-old Bayesian framework.
Guller, Ulrich +5 more
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Approximate Bayesian inference for analysis of spatiotemporal flood frequency data [PDF]
, 2022 This is the final version. Available from the Institute of Mathematical Statistics via the DOI in this recordExtreme floods cause casualties and widespread damage to property and vital civil infrastructure.
Bakka, H +9 more
core +1 more source
The Bayesian Score Statistic [PDF]
We propose a novel Bayesian test under a (noninformative) Jeffreys’ prior speciï¬ca- tion. We check whether the ï¬xed scalar value of the so-called Bayesian Score Statistic (BSS) under the null hypothesis is a plausible realization from its known and ...
Kleijn, R.H., Kleibergen, F.R., Paap, R.
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Arthritis Care &Research, EarlyView.Objective Obesity, defined by body mass index (BMI) ≥30 kg/m2, is a risk factor for functional limitations in people with knee osteoarthritis (OA). However, function varies among such individuals. Our objective was to evaluate the implications of obesity subtypes on longitudinal patterns of physical functioning in people with or at risk for knee OA ...
Kristine Godziuk +7 more
wiley +1 more source
A bayesian approach for predicting with polynomial regresión of unknown degree. [PDF]
, 2003 This article presents a comparison of four methods to compute the posterior probabilities of the possible orders in polynomial regression models. These posterior probabilities are used for forecasting by using Bayesian model averaging.
Guttman, Irwin +2 more
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Arthritis Care &Research, Accepted Article.Objective Youth who experience a sport‐related knee injury have elevated odds of overweight or obesity in 3‐10 years, compounding their risk for post‐traumatic osteoarthritis (PTOA). To inform prevention strategies, this study compared patterns of adiposity change between youth with a sport‐related knee injury and uninjured youth in the 2‐year period ...
Justin M. Losciale +6 more
wiley +1 more source
Bayesian parametric bootstrap for models with intractable likelihoods [PDF]
, 2019 In this paper it is demonstrated how the Bayesian parametric bootstrap can be adapted to models with intractable likelihoods. The approach is most appealing when the computationally efficient semi-automatic approximate Bayesian computation (ABC) summary ...
Christopher C. Drovandi +8 more
core +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
Advanced Engineering Materials, EarlyView.This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Bayesian curve estimation by model averaging [PDF]
, 2003 A bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the ...
Peña, Daniel, Redondas, María Dolores
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