The influence of misspecified covariance on false discovery control when using posterior probabilities
Ye Liang,
Joshua D. Habiger and
Xiaoyi Min
Statistical Theory and Related Fields, 2017, vol. 1, issue 2, 205-215
Abstract:
This paper focuses on the influence of a misspecified covariance structure on false discovery rate for the large-scale multiple testing problem. Specifically, we evaluate the influence on the marginal distribution of local false discovery rate statistics, which are used in many multiple testing procedures and related to Bayesian posterior probabilities. Explicit forms of the marginal distributions under both correctly specified and incorrectly specified models are derived. The Kullback–Leibler divergence is used to quantify the influence caused by a misspecification. Several numerical examples are provided to illustrate the influence. A real spatio-temporal data on soil humidity is discussed.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/24754269.2017.1387445 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tstfxx:v:1:y:2017:i:2:p:205-215
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tstf20
DOI: 10.1080/24754269.2017.1387445
Access Statistics for this article
Statistical Theory and Related Fields is currently edited by Zhao Wei
More articles in Statistical Theory and Related Fields from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().