Minimum density power divergence estimator for covariance matrix based on skew $$t$$ t distribution

Byungsoo Kim () and Sangyeol Lee ()

Statistical Methods & Applications, 2014, vol. 23, issue 4, 565-575

Abstract: In this paper, we study the problem of estimating the covariance matrix of stationary multivariate time series based on the minimum density power divergence method that uses a multivariate skew $$t$$ t distribution family. It is shown that under regularity conditions, the proposed estimator is strongly consistent and asymptotically normal. A simulation study is provided for illustration. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Minimum density power divergence; Robust estimation; Covariance matrix; Skew $$t$$ t distribution (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10260-014-0284-5

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