Results 51 to 60 of about 396,010 (290)

Spatial mixture modeling for analyzing a rainfall pattern: A case study in Ireland

Open Engineering, 2022
This study investigates the spatial heterogeneity in the maximum monthly rainfall amounts reported by stations in Ireland from January 2018 to December 2020. The heterogeneity is modeled by the Bayesian normal mixture model with different ranks.
Hussein Amjad, Kadhem Safaa K.
doaj   +1 more source

Characterizing Entanglement Sources [PDF]

, 2009
We discuss how to characterize entanglement sources with finite sets of measurements. The measurements do not have to be tomographically complete, and may consist of POVMs rather than von Neumann measurements.
B. A. Berg, C. P. Robert, G. Claeskens, J. S. Bell, K. P. Burnham, Pavel Lougovski, S. J. van Enk   +6 more
core   +2 more sources

Empirical evaluation of fully Bayesian information criteria for mixture IRT models using NUTS

Behaviormetrika, 2022
AbstractThis study is to evaluate the performance of fully Bayesian information criteria, namely, LOO, WAIC and WBIC in terms of the accuracy in determining the number of latent classes of a mixture IRT model while comparing it to the conventional model via non-random walk MCMC algorithms and to further compare their performance with conventional ...
Rehab AlHakmani, Yanyan Sheng
openaire   +1 more source

Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito, Chiara Meneghini, Alice Galli, Luca Gallo, Pierfrancesco Mitrotti, Paola Dimartino, Marianna Inglese, Cinzia Zatti, Alessandro Lupini, Andrea Pilotto, Alessandro Padovani, Micol Avenali, Enza Maria Valente, Cristina Tassorelli, Silvia P. Caminiti   +14 more
wiley   +1 more source

Comparative evaluation of score criteria for dynamic Bayesian Network structure learning.

PLoS ONE
Dynamic Bayesian Networks (DBNs) are probabilistic models with a directional structure employed to model temporal processes. Three approaches to DBN structure learning are constraint-based, score-based, and hybrid.
Aslı Yaman, Mehmet Ali Cengiz
doaj   +1 more source

Experimental Design for Nonlinear Problems

Sultan Qaboos University Journal for Science, 2007
Experimental designs for nonlinear problems have to a large extent relied on optimality criteria originally proposed for linear models. Optimal designs obtained for nonlinear models are functions of the unknown model parameters.
K.M Abdelbasit
doaj   +1 more source

Information Disclosure for Increasing User Satisfaction From a Shared Ride

IEEE Access, 2023
On-demand ridesharing services play a crucial part in the development of modern smart cities. Unfortunately, despite their advantages, not many people opt to use them.
David Zar, Noam Hazon, Amos Azaria
doaj   +1 more source

Quantifying the Impact of Ocrelizumab on Paramagnetic Rim Lesions in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Paramagnetic rim lesions (PRLs) are a subset of chronic active multiple sclerosis (MS) lesions marked by iron‐laden microglia and macrophages. Ocrelizumab, a monoclonal antibody targeting CD20+ B cells, suppresses acute MS activity, but its effect on PRLs remains unclear. In a longitudinal study of 29 ocrelizumab‐treated patients with at least
Kimberly H. Markowitz, Neha V. Safi, Iliana Pliska‐Bloch, Ulrike W. Kaunzner, Ha Luu, Yi Wang, Thanh D. Nguyen, Sandra Hurtado Rúa, Susan A. Gauthier   +8 more
wiley   +1 more source

Comparison of Criteria for Choosing the Number of Classes in Bayesian Finite Mixture Models. [PDF]

PLoS ONE, 2017
Identifying the number of classes in Bayesian finite mixture models is a challenging problem. Several criteria have been proposed, such as adaptations of the deviance information criterion, marginal likelihoods, Bayes factors, and reversible jump MCMC ...
Kazem Nasserinejad, Joost van Rosmalen, Wim de Kort, Emmanuel Lesaffre   +3 more
doaj   +1 more source

A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation [PDF]

, 2013
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., Nunes, M. A., Prangle, D., Sisson, S. A.   +3 more
core   +4 more sources