Naive, robust or fully-adaptive: An estimation problem for CES distributions

Maria S. Greco; Stefano Fortunati; Fulvio Gini

doi:10.1109/SAM.2014.6882441

Naive, robust or fully-adaptive: An estimation problem for CES distributions

Maria S. Greco, Stefano Fortunati, Fulvio Gini

University of Pisa

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

Abstract

In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cramér-Rao Bounds and Huber limit.

Original language	English
Title of host publication	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Publisher	IEEE Computer Society
Pages	457-460
Number of pages	4
ISBN (Print)	9781479914814
DOIs	https://doi.org/10.1109/SAM.2014.6882441
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 - A Coruna, Spain Duration: 22 Jun 2014 → 25 Jun 2014

Publication series

Name	Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)	2151-870X

Conference

Conference	2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014
Country/Territory	Spain
City	A Coruna
Period	22/06/14 → 25/06/14

Access to Document

10.1109/SAM.2014.6882441

Cite this

Greco, M. S., Fortunati, S., & Gini, F. (2014). Naive, robust or fully-adaptive: An estimation problem for CES distributions. In 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 (pp. 457-460). Article 6882439 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop). IEEE Computer Society. https://doi.org/10.1109/SAM.2014.6882441

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title = "Naive, robust or fully-adaptive: An estimation problem for CES distributions",

abstract = "In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cram{\'e}r-Rao Bounds and Huber limit.",

author = "Greco, \{Maria S.\} and Stefano Fortunati and Fulvio Gini",

year = "2014",

month = jan,

day = "1",

doi = "10.1109/SAM.2014.6882441",

language = "English",

isbn = "9781479914814",

series = "Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop",

publisher = "IEEE Computer Society",

pages = "457--460",

booktitle = "2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014",

note = "2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014 ; Conference date: 22-06-2014 Through 25-06-2014",

}

Greco, MS, Fortunati, S & Gini, F 2014, Naive, robust or fully-adaptive: An estimation problem for CES distributions. in 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014., 6882439, Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, IEEE Computer Society, pp. 457-460, 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014, A Coruna, Spain, 22/06/14. https://doi.org/10.1109/SAM.2014.6882441

Naive, robust or fully-adaptive: An estimation problem for CES distributions. / Greco, Maria S.; Fortunati, Stefano; Gini, Fulvio.
2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop, SAM 2014. IEEE Computer Society, 2014. p. 457-460 6882439 (Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop).

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

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N2 - In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cramér-Rao Bounds and Huber limit.

AB - In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cramér-Rao Bounds and Huber limit.

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DO - 10.1109/SAM.2014.6882441

M3 - Conference contribution

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Naive, robust or fully-adaptive: An estimation problem for CES distributions

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