A comparative study of data transformations for wavelet shrinkage estimation with application to software reliability assessment
A comparative study of data transformations for wavelet shrinkage estimation with application to software reliability assessment
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小波收缩估计数据变换与软件可靠性评估的比较研究
DOI：
10.1155/2012/524636
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Xiao XIAO and Tadashi DOHI
中科院分区：
文献类型：
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作者：
H. Okamura;T. Hirata and T. Dohi;下川原健，竹野健夫，堀川三好，菅原光政;H. Okamura and T. Dohi;竹野健夫，堀川三好;X. Xiao and T. Dohi;Xiao XIAO and Tadashi DOHI
在我们之前的工作中，我们提出了基于非齐次泊松过程（NHPP）的软件可靠性模型（SRMs）的小波收缩估计（WSE），其中WSE是一种基于数据变换的非参数估计方法。在许多方差稳定的数据变换中，采用了Anscombe变换和Fisz变换。我们已经证明，在许多情况下，它可以提供比传统的最大似然估计（MLE）和最小二乘估计（LSE）更高的拟合优度性能，尽管它是非参数的性质，通过实际软件故障计数数据的数值实验。为了提高WSE的估计精度，本文引入了另外三种数据变换对软件故障计数数据进行预处理，并通过拟合优度检验研究了不同数据变换对WSE估计精度的影响。
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.