An alternative to the analysis of variance for reliability data

Though the analysis of variance is a commonly applied method for testing for differences between means of several processes, it is based in part on the assumption that the processes give rise to output that is normally distributed on the measured variable. Reliability and life test studies frequently give birth to data that exhibit clear skew, and application of the analysis of variance is questionable in such cases. A method referred to as analysis of reciprocals, which is based on an assumed inverse Gaussian distribution, provides an alternative to the analysis of variance in these instances. With applications in a variety of functional areas, including reliability and life testing, the inverse Gaussian distribution is able to accommodate substantial skew. It is hoped that this exposition will increase awareness of both the inverse Gaussian distribution and data analysis methods that are based on this distribution.     

L~p[-1,1](1p<∞)空间中复系数多项式的倒数逼近

讨论了Lp[-1,1](1 p<∞)空间函数的复系数多项式的倒数逼近问题,证明了如下结论:设f(x)∈Lp[-1,1](1 p<∞),则存在一个次数不超过3n的复系数多项式Q3n(x)及一个仅与p有关的常数Mp>0使得　　f(x)-1Q3n(x)Lp[-1,1] Mpωφ(f,1 n)L2p