MCMC design-based non-parametric regression for rare event. application to nested risk computations

DOI10.1515/mcma-2017-0101zbMath1360.65024OpenAlexW2585015364MaRDI QIDQ515537

Emmanuel Gobet, Gersende Fort, Eric Moulines

Publication date: 16 March 2017

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mcma-2017-0101

zbMATH Keywords

algorithmnumerical resultserror boundleast squares methodfinancial riskrare eventnon-parametric regressionempirical regression schemeMarkov chain Monte Carlo sampler

Mathematics Subject Classification ID

Related Items (4)

Technical Note—Bootstrap-based Budget Allocation for Nested Simulation ⋮ Kernel quantile estimators for nested simulation with application to portfolio value-at-risk measurement ⋮ Quantitative bounds for concentration-of-measure inequalities and empirical regression: the independent case ⋮ Transform MCMC schemes for sampling intractable factor copula models

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