Carmin.tv

Mathematics
and Interactions

Please leave your feedback in order for us to improve your experience !
Arithmetic Geometry – A Conference in Honor of Hélène Esnault on the Occasion of Her 70th Birthday
12 videos

Arithmetic Geometry – A Conference in Honor of Hélène Esnault on the Occasion of Her 70th Birthday

Not Only Scalar Curvature Seminar
58 videos

Not Only Scalar Curvature Seminar

Clément Delcamp : Topological Symmetry and Duality in Quantum Lattice Models
2 videos

Clément Delcamp : Topological Symmetry and Duality in Quantum Lattice Models

Lean for the curious mathematician / Lean pour mathématiciens
4 videos

Lean for the curious mathematician / Lean pour mathématiciens

All the collections
CIMPA
CIRM
IHES
IHP
LMR
SMF
All the institutions
Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Collection Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2

Organizer(s) Bogdan, Malgorzata ; Graczyk, Piotr ; Panloup, Fabien ; Proïa, Frédéric ; Roquain, Etienne
Date(s) 15/06/2020 - 19/06/2020
linked URL https://www.cirm-math.com/cirm-virtual-event-2146.html
00:00:00 / 00:00:00
8 25

Optimal control of false discovery criteria in the general two-group model

By Ruth Heller

The highly influential two-group model in testing a large number of statistical hypotheses assumes that the test statistics are drawn independently from a mixture of a high probability null distribution and a low probability alternative. Optimal control of the marginal false discovery rate (mFDR), in the sense that it provides maximal power (expected true discoveries) subject to mFDR control, is known to be achieved by thresholding the local false discovery rate (locFDR), i.e., the probability of the hypothesis being null given the set of test statistics, with a fixed threshold. We address the challenge of controlling optimally the popular false discovery rate (FDR) or positive FDR (pFDR) rather than mFDR in the general two-group model, which also allows for dependence between the test statistics. These criteria are less conservative than the mFDR criterion, so they make more rejections in expectation. We derive their optimal multiple testing (OMT) policies, which turn out to be thresholding the locFDR with a threshold that is a function of the entire set of statistics. We develop an efficient algorithm for finding these policies, and use it for problems with thousands of hypotheses. We illustrate these procedures on gene expression studies.

Information about the video

Citation data

  • DOI 10.24350/CIRM.V.19640903
  • Cite this video Heller, Ruth (03/06/2020). Optimal control of false discovery criteria in the general two-group model. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19640903
  • URL https://dx.doi.org/10.24350/CIRM.V.19640903

Domain(s)

Bibliography

  • ROSSET, Saharon. Optimal control of false discovery criteria in the two-group model. arXiv preprint arXiv:1902.00892, 2019. - https://arxiv.org/abs/1902.00892

MSC codes

Document(s)

Last related questions on MathOverflow

You have to connect your Carmin.tv account with mathoverflow to add question

Ask a question on MathOverflow




Register

  • Bookmark videos
  • Add videos to see later &
    keep your browsing history
  • Comment with the scientific
    community
  • Get notification updates
    for your favorite subjects
Copyright Carmin.tv 2024
By browsing our website, you accept the use of cookies to improve your experience. Find out more about our privacy policy.
Approve
Give feedback