Majeske, Lynch-Caris and Herrin [1] show how automobile manufacturers apply statistical models to warranty data to make inference regarding product design changes. Manufacturers also use warranty data to compare actual field performance with pseudo-lifetime data generated in laboratory or bench test settings Majeske ,Lynch-Caris 和 Herrin(估计是三个公司的名字)为我们展示了如何用统计学模型分析从质量保证书上反馈回来的数据，并且借此对如何更改产品设计作出推断。同时，厂商们也经常把质量保证书上的信息和实际使用情况信息，还有实验室里的推测使用情况信息，这三组数据做比较。[2]. Automobile manufacturers provide customers with a basic two-dimensional warranty that quantifies vehicle lifetime with two metrics: time and mileage. However, many manufacturers model field performance in the time domain due to the uncertainty associated with mileage accumulation. 汽车制造商们提供给顾客一种二维的质量保证。这种二维质量保证从两个方面描述了一两汽车的使用寿命情况，第一个方面是从运行时间方面，第二个方面是从运行的公里数上来体现。但是，大多数厂家习惯以运行时间这种方式来衡量一辆车，因为如果用另一种方法，则有很多可能的误差。Wasserman [3] and Robinson and McDonald [4] define the statistic RetT-claims per thousand vehicles reported cumulatively by month in service-a non-parametric model that automobile manufacturers use to track warranty performance. Wasserman [3] develops a dynamic linear predictive model for RetT using data from multiple model years of a given vehicle.Wasserman和Robinson&McDonald这两家公司通过对RetT反馈回来每月车辆数据（千辆为单位）的信息（RetT-regional transport&tourism----地方交通旅（游管理局）），把这些信息用一种叫service-a non-parametric的模型来统计分析。Wasserman为RetT研发了一种活动连接预测模型来分析某种车型多年的积累数据。___________实在对不起,后面的我放弃了，太多专业词汇了...非我力所能及.抱歉啊
