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    Bootstrap-assisted tests of symmetry for dependent data

    Psaradakis, Zacharias and Vávra, M. (2019) Bootstrap-assisted tests of symmetry for dependent data. Journal of Statistical Computation and Simulation 89 (7), pp. 1203-1226. ISSN 0094-9655.

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    Abstract

    The paper considers the problem of testing for symmetry (about an unknown centre) of the marginal distribution of a strictly stationary and weakly dependent stochastic process. The possibility of using the autoregressive sieve bootstrap and stationary bootstrap procedures to obtain critical values and P-values for symmetry tests is explored. Bootstrap-assisted tests for symmetry are straightforward to implement and require no prior estimation of asymptotic variances. The small-sample properties of a wide variety of tests are investigated using Monte Carlo experiments. A bootstrap-assisted version of the triples test is found to have the best overall performance.

    Metadata

    Item Type: Article
    Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis, available online at the link above.
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Depositing User: Zacharias Psaradakis
    Date Deposited: 25 Jan 2019 09:11
    Last Modified: 01 Feb 2020 00:15
    URI: http://eprints.bbk.ac.uk/id/eprint/25997

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