Quasi-Bayesian software reliability model with small samples

Autor:	Junxiang Tu, Jin Zhang, Zhuoning Chen, Xiao-guang Yan
Rok vydání:	2009
Předmět:	Software reliability model Computer science General Mathematics Bayesian probability General Engineering Mechatronics Empirical probability Imprecise probability computer.software_genre Software quality Bayesian statistics Probability distribution Data mining computer
Zdroj:	Journal of Shanghai University (English Edition). 13:301-304
ISSN:	1863-236X 1007-6417
DOI:	10.1007/s11741-009-0410-1
Popis:	In traditional Bayesian software reliability models, it was assume that all probabilities are precise. In practical applications the parameters of the probability distributions are often under uncertainty due to strong dependence on subjective information of experts’ judgments on sparse statistical data. In this paper, a quasi-Bayesian software reliability model using interval-valued probabilities to clearly quantify experts’ prior beliefs on possible intervals of the parameters of the probability distributions is presented. The model integrates experts’ judgments with statistical data to obtain more convincible assessments of software reliability with small samples. For some actual data sets, the presented model yields better predictions than the Jelinski-Moranda (JM) model using maximum likelihood (ML).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::94fd13dce30116cb1abf02aa29552133 https://doi.org/10.1007/s11741-009-0410-1 Zobrazit plný text záznamu Full text from SpringerLink