无法估计的

Univariate indices are not adequate for assessing the capability of processes with multiple characteristics. Among all developed multivariate process capabilities, index has the most accurate estimation of Cpm. takes into account both the ratio of the tolerance region to the process region and the probability of nonconforming product. However, the exact probability distribution of is too complicated to be derived. Consequently, the related hypothesis testing and confidence interval cannot be developed.

在众多的指标当中，单变量制程能力指标的发展已趋成熟，而多品质特性的制程能力指标还在持续的发展中，其中多品质特性制程能力指标是所有多品质制程能力指标中估计值最准确的指标，但在利用多品质制程能力指标Cpm来评选两个制程的制程能力时，由於指标之机率分配过於复杂，迄今未能推导出其相关的统计假说检定或信赖区间，因此无法发展出检定两个制程能力指标Cpm是否有差异的统计检定程序。

Multiple linear regression is the simplest way to build the relationship between the several explanatory variables and response variable. However, MLR often causes the estimated regression coefficients unstable or even unaccessible when the number of explanatory variables is more than that of objects. Especially, the explanatory variables are highly intercorrelated which called multi-collinear data. Therefore, many methods have been developed to analyze multi-collinear data, such as variable selection methods, ridge regression, principal components regression and partial least squares regression.

当要同时建立多个解释变数与反应变数间的关系时，最简单的方式是以复回归来处理，但是当解释变数数目远多於样本数，或者变数之间具有高度相关性时，会使得回归系数的估计变得不稳定甚至无法求得，这样的资料又称为共线性资料，在面临这样的资料时可以利用变数选取的方式降低资料组的维度，或者以脊回归、主成分回归及净最小平方回归等方法来灭种共线性的干扰。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。