On inconsistency of estimators of parameters of non-homogeneous Poisson process models for software reliability

Tapan K. Nayak, Sudip Bose and Subrata Kundu

Statistics & Probability Letters, 2008, vol. 78, issue 14, 2217-2221

Abstract: Non-homogeneous Poisson Process (NHPP) models form a significant subclass of the many software reliability models proposed in the literature. We prove an important limitation of NHPP models for which the expected number of failures in infinite testing is finite. Specifically, the parameters of those models cannot be estimated consistently as the testing time approaches infinity. We also discuss certain parameter-based asymptotic properties of the maximum likelihood estimators of the model parameters and some logical implications of NHPP model assumptions.

Date: 2008
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(08)00113-2
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:stapro:v:78:y:2008:i:14:p:2217-2221

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().