An inverse Laplace transform oracle estimator for the normal means problem

Adebowale J. Sijuwade (), Swarnita Chakraborty and Nairanjana Dasgupta
Additional contact information
Adebowale J. Sijuwade: Washington State University
Swarnita Chakraborty: Washington State University
Nairanjana Dasgupta: Washington State University

Metrika: International Journal for Theoretical and Applied Statistics, 2024, vol. 87, issue 5, No 3, 533-550

Abstract: Abstract In an effort to estimate the number of true nulls in large scale multiplicity problems (the normal means problem), we generalize the current Fourier transform based oracle estimator with a Laplace transform based estimator. Our interest in this problem stems from the application of r-power which requires knowledge of the number of nulls (Dasgupta et al. in Sankhya B 78(1):96–118, 2016). We analytically show that our method is consistent and theoretically has lower mean squared error than the existing competitor (Jin in J R Stat Soc Ser B (Stat Methodol) 70(3):461–493, 2008). We follow up by a numerical example and a simulation study that ratifies our theoretical results.

Keywords: Multiplicity; Bilateral Laplace transform; Fourier transform; r-Power (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00184-023-00922-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:metrik:v:87:y:2024:i:5:d:10.1007_s00184-023-00922-4

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s00184-023-00922-4

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().