Results 61 to 70 of about 548,736 (273)
Adaptive Bayesian estimation using a Gaussian random field with inverse Gamma bandwidth [PDF]
We consider nonparametric Bayesian estimation inference using a rescaled smooth Gaussian field as a prior for a multidimensional function. The rescaling is achieved using a Gamma variable and the procedure can be viewed as choosing an inverse Gamma ...
van der Vaart, A. W., van Zanten, J. H.
core +6 more sources
High Healthcare Utilization Preceding Diagnosis with Juvenile Idiopathic Arthritis
Objective Though early diagnosis improves long‐term outcomes, Juvenile Idiopathic Arthritis (JIA) patients often experience prolonged, circuitous paths to diagnosis. To inform diagnostic improvement, we sought to characterize healthcare utilization in the year preceding diagnosis.
Anna Costello +5 more
wiley +1 more source
A Bayesian Approach to the Naming Game Model
We present a novel Bayesian approach to semiotic dynamics, which is a cognitive analog of the naming game model restricted to two conventions. The model introduced in this paper provides a general framework for studying the combined effects of cognitive ...
Gionni Marchetti +2 more
doaj +1 more source
Nonparametric Bayesian multiple testing for longitudinal performance stratification
This paper describes a framework for flexible multiple hypothesis testing of autoregressive time series. The modeling approach is Bayesian, though a blend of frequentist and Bayesian reasoning is used to evaluate procedures.
Scott, James G.
core +1 more source
Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis
Objectives We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham +14 more
wiley +1 more source
Non-linear regression models for Approximate Bayesian Computation
Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable.
A. Butler +43 more
core +1 more source
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 Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation [PDF]
Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions.
Blum, M. G. B. +3 more
core +4 more sources
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
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
Nanoindentation Criteria for Combinatorial Thin Film Libraries
Thin‐film material libraries are compositional spreads used for screening composition‐structure‐property relationships. Nanoindentation is often used to characterize mechanical behavior across these systems, however variations in methodology are widespread.
Andre Bohn, Adie Alwen, Andrea M. Hodge
wiley +1 more source

