A Monte Carlo evaluation of the performance of two new tests for symmetry
James S. Allison () and
Charl Pretorius
Additional contact information
James S. Allison: North-West University
Charl Pretorius: North-West University
Computational Statistics, 2017, vol. 32, issue 4, No 5, 1323-1338
Abstract:
Abstract We propose two new tests for symmetry based on well-known characterisations of symmetric distributions. The performance of the new tests is evaluated and compared to that of other existing tests by means of a Monte Carlo study. All tests are carried out in a regression setup where we test whether the error distribution in a linear regression model is symmetric. It is found that the newly proposed tests perform favourably compared to the other tests.
Keywords: Characterisation of symmetry; Empirical characteristic function; Goodness-of-fit (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://link.springer.com/10.1007/s00180-016-0680-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:32:y:2017:i:4:d:10.1007_s00180-016-0680-4
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2
DOI: 10.1007/s00180-016-0680-4
Access Statistics for this article
Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik
More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().