Computational statistics harnesses the power of sophisticated numerical algorithms and high‐performance computing to solve complex inferential problems that are intractable by traditional analytical ...
Bayesian statistics represents a powerful framework for data analysis that centres on Bayes’ theorem, enabling researchers to update existing beliefs with incoming evidence. By combining prior ...
In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...
Abstract: Computational Bayesian inference offers a flexible approach to answering important scientific questions regarding uncertainty. However, the Bayesian approach can reach its computational ...
Brazilian Journal of Probability and Statistics, Vol. 27, No. 1 (February 2013), pp. 1-19 (19 pages) We introduce a Bayesian analysis for beta generalized distributions and related exponentiated ...
The paper presents a Bayesian framework for the calibration of financial models using neural stochastic differential equations (neural SDEs), for which we also formulate a global universal ...
Email: [email protected] Phone: (804) 684-7221 Interests: Bayesian / hierarchical / spatial / temporal / mixed-effects modeling of complex environmental / ecological / biological phenomena; statistical ...
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