A Comparative Study of Data Transformations for Wavelet Shrinkage Estimation with Application to Software Reliability Assessment. (13th May 2012)

• Record Type: Journal Article
• Authors: Xiao, Xiao; Dohi, Tadashi
• Other Names: Huang Chin-Yu Academic Editor.
• Is Part Of: Advances in software engineering. Volume 2012(2012)
• Publication Date: 2012-05-13
• Subjects: Software engineering -- Periodicals; Software engineering; Periodicals; Electronic journals; 005.1
• DOI: 10.1155/2012/524636
• Languages: English
• ISSNs: 1687-8655

Abstract

Abstract : In our previous work, we proposed wavelet shrinkage estimation (WSE) for nonhomogeneous Poisson process (NHPP)-based software reliability models (SRMs), where WSE is a data-transform-based nonparametric estimation method. Among many variance-stabilizing data transformations, the Anscombe transform and the Fisz transform were employed. We have shown that it could provide higher goodness-of-fit performance than the conventional maximum likelihood estimation (MLE) and the least squares estimation (LSE) in many cases, in spite of its non-parametric nature, through numerical experiments with real software-fault count data. With the aim of improving the estimation accuracy of WSE, in this paper we introduce other three data transformations to preprocess the software-fault count data and investigate the influence of different data transformations to the estimation accuracy of WSE through goodness-of-fit test.