On maximum likelihood estimation for a general non-homogeneous Poisson process
研究了时间截断抽样下参数化非齐次泊松过程软件可靠性模型的最大似然估计，发现估计量不一定具有一致性和渐近正态性，并推导了特定模型的渐近分布。
Non-homogeneous Poisson processes (NHPPs) have been widely used in the study of software reliability. The statistical analysis for NHPPs is of interest to both theoreticians and practitioners. In this paper, maximum likelihood estimation under time-truncated sampling is studied for parametric NHPP software reliability models with bounded mean value functions. It is shown that the maximum likelihood estimators need not be consistent or asymptotically normal. The asymptotic distribution is derived for a specific NHPP model.