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 Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Zacharias Psaradakis |
| Date Deposited: | 25 Jan 2019 09:11 |
| Last Modified: | 02 Aug 2023 17:47 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/25997 |
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