Measure-Transformed Gaussian quasi score test

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


In this paper, we develop a robust generalization of the Gaussian quasi score test (GQST) for composite binary hypothesis testing. The proposed test, called measure-transformed GQST (MT-GQST), is based on a transformation applied to the probability distribution of the data. The considered transform is structured by a non-negative function, called MT-function, that weights the data points. By appropriate selection of the MTfunction we show that, unlike the GQST, the proposed MT-GQST incorporates higher-order moments and can gain robustness to outliers. The MT-GQST is applied for testing the parameter of a non-linear model. Simulation example illustrates its advantages as compared to the standard GQST and other robust detectors.

Original languageEnglish
Title of host publication25th European Signal Processing Conference, EUSIPCO 2017
PublisherInstitute of Electrical and Electronics Engineers
Number of pages5
ISBN (Electronic)9780992862671
StatePublished - 23 Oct 2017
Event25th European Signal Processing Conference, EUSIPCO 2017 - Kos, Greece
Duration: 28 Aug 20172 Sep 2017

Publication series

Name25th European Signal Processing Conference, EUSIPCO 2017


Conference25th European Signal Processing Conference, EUSIPCO 2017

ASJC Scopus subject areas

  • Signal Processing


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