How Pooling Failure Data May Reverse Increasing Failure Rates
研究了递增失效率分布的混合可能最终呈现递减失效率的条件，警告混合不同分布的数据可能逆转单个样本的递增失效率特性。
Abstract Although mixtures of decreasing failure rate (DFR) distributions are always DFR, some mixtures of increasing failure rate (IFR) distributions can also be ultimately DFR. In this article various types of discrete and continuous mixtures of IFR distributions are considered, and conditions are developed for such mixtures to be ultimately DFR. These conditions lead to an interesting result—that certain mixtures of IFR distributions, even those with very rapidly increasing failure rates (e.g., Weibull, truncated extreme), ultimately become DFR distributions. It is common practice to pool data from several different IFR distributions to enlarge sample size, for instance. The results of this article sound a warning that such pooling may actually reverse the IFR property of the individual samples to a DFR property.