Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract)

Tang Liu; Alex Dytso; H. Vincent Poor; Shlomo Shamai

doi:10.1109/IEEECONF56349.2022.10052066

Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract)

Tang Liu, Alex Dytso, H. Vincent Poor, Shlomo Shamai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Consider a noisy observation Y=X+N where X is a random variable, and N is a Gaussian random variable with zero mean, variance s2, independent from X. The object of this work is to construct a consistent estimator for the conditional cumulants of the random variable X given the observation Y=y, in the empirical Bayes framework. Cu-mulants are important statistical quantities that provide useful alternatives to moments and have a variety of applications [1]-[4].

Original language	English (US)
Title of host publication	56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Editors	Michael B. Matthews
Publisher	IEEE Computer Society
Pages	1036-1037
Number of pages	2
ISBN (Electronic)	9781665459068
DOIs	https://doi.org/10.1109/IEEECONF56349.2022.10052066
State	Published - 2022
Externally published	Yes
Event	56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States Duration: Oct 31 2022 → Nov 2 2022

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
Volume	2022-October
ISSN (Print)	1058-6393

Conference

Conference	56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/Territory	United States
City	Virtual, Online
Period	10/31/22 → 11/2/22

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/IEEECONF56349.2022.10052066

Cite this

Liu, T., Dytso, A., Poor, H. V., & Shamai, S. (2022). Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract). In M. B. Matthews (Ed.), 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 (pp. 1036-1037). (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2022-October). IEEE Computer Society. https://doi.org/10.1109/IEEECONF56349.2022.10052066

Liu, Tang ; Dytso, Alex ; Poor, H. Vincent et al. / Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract). 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022. editor / Michael B. Matthews. IEEE Computer Society, 2022. pp. 1036-1037 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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title = "Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract)",

abstract = "Consider a noisy observation Y=X+N where X is a random variable, and N is a Gaussian random variable with zero mean, variance s2, independent from X. The object of this work is to construct a consistent estimator for the conditional cumulants of the random variable X given the observation Y=y, in the empirical Bayes framework. Cu-mulants are important statistical quantities that provide useful alternatives to moments and have a variety of applications [1]-[4].",

author = "Tang Liu and Alex Dytso and Poor, {H. Vincent} and Shlomo Shamai",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 ; Conference date: 31-10-2022 Through 02-11-2022",

year = "2022",

doi = "10.1109/IEEECONF56349.2022.10052066",

language = "English (US)",

series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "IEEE Computer Society",

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Liu, T, Dytso, A, Poor, HV & Shamai, S 2022, Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract). in MB Matthews (ed.), 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022. Conference Record - Asilomar Conference on Signals, Systems and Computers, vol. 2022-October, IEEE Computer Society, pp. 1036-1037, 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022, Virtual, Online, United States, 10/31/22. https://doi.org/10.1109/IEEECONF56349.2022.10052066

Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract). / Liu, Tang; Dytso, Alex; Poor, H. Vincent et al.
56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022. ed. / Michael B. Matthews. IEEE Computer Society, 2022. p. 1036-1037 (Conference Record - Asilomar Conference on Signals, Systems and Computers; Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Consider a noisy observation Y=X+N where X is a random variable, and N is a Gaussian random variable with zero mean, variance s2, independent from X. The object of this work is to construct a consistent estimator for the conditional cumulants of the random variable X given the observation Y=y, in the empirical Bayes framework. Cu-mulants are important statistical quantities that provide useful alternatives to moments and have a variety of applications [1]-[4].

AB - Consider a noisy observation Y=X+N where X is a random variable, and N is a Gaussian random variable with zero mean, variance s2, independent from X. The object of this work is to construct a consistent estimator for the conditional cumulants of the random variable X given the observation Y=y, in the empirical Bayes framework. Cu-mulants are important statistical quantities that provide useful alternatives to moments and have a variety of applications [1]-[4].

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Liu T, Dytso A, Poor HV, Shamai S. Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract). In Matthews MB, editor, 56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022. IEEE Computer Society. 2022. p. 1036-1037. (Conference Record - Asilomar Conference on Signals, Systems and Computers). doi: 10.1109/IEEECONF56349.2022.10052066

Consistent Estimation of Conditional Cumulants in the Empirical Bayes Framework (Extended Abstract)

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