An analytical model is developed for accelerated performance degradation tests. Theperformance degradations at a specified exposure time of products are assumed to follow a normal population. We assume that the relationship between the location parameter of normal population and the exposure time is a linear function of the exposure time, that is, (mu)(t) velence a + bt that the slope coefficient of the linear relationship has an Arrhenius dependence on temperature and that the scale parameter of the normal population is constant and independent of temperature or exposure time. The method of maximum likelihood estimation is used to estimate the parameters involved. A closed form expression of the likelihood function for the accelerated performance degradation data is derived and the Fisher information matrix is also derived for calculating the asymptotic variance of the 100pth percentile of the lifetime distribution at use temperature.
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机译：开发了一种分析模型，用于加速性能降解测试。假设产品的特定曝光时间的可行性降解遵循正常群体。我们假设正常群体的位置参数与曝光时间之间的关系是曝光时间的线性函数，即线性关系的斜率系数的（mu）（t）velence a + bt具有Arrhenius依赖性在温度和正常群体的比例参数是恒定的，与温度或暴露时间无关。最大似然估计的方法用于估计所涉及的参数。推导出加速性能劣化数据的闭合形式表达，并且还导出了Fisher信息矩阵，用于计算使用温度下寿命分布的100pth百分位数的渐近方差。
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