Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

article · Statistics & Probability Letters · 2010

Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors

In Hong Chang, Rahul Mukerjee

Cited by 3Abstract and details only

Abstract

The index has no abstract for this paper. The publisher’s page may have one.

Cite this paper

APA 7

Chang, I. H., & Mukerjee, R. (2010). Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors. Statistics & Probability Letters, 80(23-24), 1791–1797. https://doi.org/10.1016/j.spl.2010.08.003

MLA 9

Chang, In Hong, and Rahul Mukerjee. “Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors.” Statistics & Probability Letters, vol. 80, no. 23-24, 2010, pp. 1791–97, https://doi.org/10.1016/j.spl.2010.08.003.

Chicago

Chang, In Hong, and Rahul Mukerjee. 2010. “Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors.” Statistics & Probability Letters 80 (23-24): 1791–97. https://doi.org/10.1016/j.spl.2010.08.003.

Harvard

Chang, I.H. and Mukerjee, R. (2010) ‘Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors’, Statistics & Probability Letters, 80(23-24), pp. 1791–1797. Available at: https://doi.org/10.1016/j.spl.2010.08.003.

BibTeX
@article{chang2010highest,
  title = {{Highest posterior density regions with approximate frequentist validity: The role of data-dependent priors}},
  author = {Chang, In Hong and Mukerjee, Rahul},
  journal = {Statistics & Probability Letters},
  volume = {80},
  number = {23-24},
  pages = {1791--1797},
  year = {2010},
  doi = {10.1016/j.spl.2010.08.003}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers