Composite likelihood methods: Rao-type tests based on composite minimum density power divergence estimator

E. Castilla (), N. Martín (), L. Pardo () and K. Zografos ()
Additional contact information
E. Castilla: Complutense University of Madrid
N. Martín: Complutense University of Madrid
L. Pardo: Complutense University of Madrid
K. Zografos: University of Ioannina

Statistical Papers, 2021, vol. 62, issue 2, No 19, 1003-1041

Abstract: Abstract This paper is aimed to present a robust extension of the classical Rao test statistic, in the context of composite likelihood ideas and methods. The Rao-type test statistics are defined on the basis of the composite minimum power divergence estimators instead of the composite maximum likelihood estimator. These Rao-type test statistics are used to test simple and composite null hypotheses. Their performance is evaluated in terms of a simulation study which concentrates to the robustness and the comparison of the Rao-type tests with the respective Wald-type tests considered in Castilla et al. (Entropy 20:18, 2018). The proposed here procedures are developed on the basis of the restricted composite minimum density power divergence estimators which are also discussed for the sake of completeness.

Keywords: Composite likelihood; Composite minimum density power divergence estimators; Restricted composite minimum density power divergence estimators; Rao-type test statistics (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00362-019-01122-x

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