A test for the geometric distribution based on linear regression of order statistics

M.D. Jiménez-Gamero and M.V. Alba-Fernández

Mathematics and Computers in Simulation (MATCOM), 2021, vol. 186, issue C, 103-123

Abstract: This paper proposes and studies a novel test for the geometric distribution which is based on a characterization of that law in terms of the conditional expectation of the second order statistic, given the value of the first order statistic. The asymptotic null distribution of the test statistic and its limit under general conditions are derived, proving that it is consistent against fixed alternatives. It can also detect alternatives converging to the null at the rate n−1∕2, n denoting the sample size. A weighted bootstrap and a parametric bootstrap can be used to consistently estimate the null distribution. The finite sample performance of these two bootstrap approximations is assessed via simulation. The power of the new test is numerically compared with that of some existing tests, concluding that the proposal presents a competitive behavior.

Keywords: Geometric law; Order statistics; Goodness-of-fit; Bootstrap (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475420302901
Full text for ScienceDirect subscribers only

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:eee:matcom:v:186:y:2021:i:c:p:103-123

DOI: 10.1016/j.matcom.2020.08.023

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().