Academic Journal

Nested sampling for physical scientists

التفاصيل البيبلوغرافية
العنوان: Nested sampling for physical scientists
المؤلفون: Ashton, G., Bernstein, N., Buchner, J., Chen, X., Csányi, G., Fowlie, A., Feroz, F., Griffiths, M., Handley, W., Habeck, M., Higson, E., Hobson, M., Lasenby, A., Parkinson, D., Pártay, L., Pitkin, M., Schneider, D., Speagle, J., South, L., Veitch, J., Wacker, P., Yallup, D.
المصدر: Nature Reviews Methods Primers
سنة النشر: 2022
المجموعة: Max Planck Society: MPG.PuRe
الوصف: This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions surveyed, including methods for sampling from the constrained prior. Different ways of applying nested sampling are outlined, with detailed examples from three scientific fields: cosmology, gravitational-wave astronomy and materials science. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: unknown
Relation: http://hdl.handle.net/21.11116/0000-000C-A9EE-A; http://hdl.handle.net/21.11116/0000-000C-A9F0-6
الاتاحة: http://hdl.handle.net/21.11116/0000-000C-A9EE-A
http://hdl.handle.net/21.11116/0000-000C-A9F0-6
Rights: info:eu-repo/semantics/closedAccess
رقم الانضمام: edsbas.989402F7
قاعدة البيانات: BASE