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Robust quadratic discriminant analysis using Sn covariance

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dc.contributor.author Sajana, OK
dc.contributor.author Sajesh, TA
dc.date.accessioned 2022-02-16T10:54:45Z
dc.date.available 2022-02-16T10:54:45Z
dc.date.issued 2021-03-15
dc.identifier.citation O. K. Sajana & T. A. Sajesh (2021) Robust quadratic discriminant analysis using Sn covariance, Communications in Statistics - Simulation and Computation en_US
dc.identifier.other 10.1080/03610918.2020.1868512
dc.identifier.uri http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/55
dc.description.abstract This paper presents a robust method for robust estimation of quadratic discriminant analysis. The mean and covariance matrix for estimating quadratic discriminant rule is computed using a robust estimation method called Sn method established from a robust covariance estimator SnCov. The performance of the proposed method is evaluated using the results of simulated samples. This outlier detection method is compared with some well-known methods available in the current literature. The application of the proposed method in real-life data is also executed in this paper. en_US
dc.language.iso en en_US
dc.publisher Taylor & Francis en_US
dc.subject Multivariate data en_US
dc.subject Quadratic discriminant rule en_US
dc.subject Robust estimation en_US
dc.title Robust quadratic discriminant analysis using Sn covariance en_US
dc.type Article en_US


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