Psaradakis, Zacharias and Vavra, Marian (2017) A distance test of normality for a wide class of stationary processes. Econometrics and Statistics 2 , pp. 50-60. ISSN 2452-3062.
|
Text
Normality_E&S.pdf - Author's Accepted Manuscript Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (320kB) | Preview |
Abstract
A distance test for normality of the one-dimensional marginal distribution of stationary fractionally integrated processes is considered. The test is implemented by using an autoregressive sieve bootstrap approximation to the null sampling distribution of the test statistic. The bootstrap-based test does not require knowledge of either the dependence parameter of the data or of the appropriate norming factor for the test statistic. The small-sample properties of the test are examined by means of Monte Carlo experiments. An application to real-world data is also presented.
Metadata
Item Type: | Article |
---|---|
Keyword(s) / Subject(s): | Distance test, Fractionally integrated process, Sieve bootstrap, Normality |
School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
Depositing User: | Zacharias Psaradakis |
Date Deposited: | 17 Jan 2017 14:51 |
Last Modified: | 02 Aug 2023 17:29 |
URI: | https://eprints.bbk.ac.uk/id/eprint/17547 |
Statistics
Additional statistics are available via IRStats2.