PARTIAL LEAST SQUARES ANALYSIS WITH CROSS-VALIDATION FOR THE TWO-CLASS PROBLEM A MONTE CARLO STUDY
PARTIAL LEAST SQUARES ANALYSIS WITH CROSS-VALIDATION FOR THE TWO-CLASS PROBLEM A MONTE CARLO STUDY
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DOI：
10.1002/cem.1180010306
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发表时间：
1987-01-01
影响因子：
2.4
通讯作者：
WOLD S
中科院分区：
文献类型：
--
作者：
STAHLE L;WOLD S
研究了两个独立样本在位置上的差异的统计分析方法。该方法使用偏最小二乘投影对潜在结构（PLS）进行交叉验证。讨论了与经典方法的关系，并进行了蒙特卡罗研究，以描述所采用的检验统计量的分布如何取决于对象的数量、变量的数量、由第一个pls分量解释的百分比方差和缺失值的百分比。给出了检验统计量的50%和5%水平对这些因素的依赖性的多项式近似。50%水平的多项式是复杂的，涉及几个一、二、三度项，而5%水平的多项式仅取决于对象的数量和第一个组件的大小。一个单独的蒙特卡罗实验表明，样本大小的适度差异不会影响检验统计量的分布。对多样本定位问题进行了研究，并通过仿真验证了增加样本数量对测试统计量的影响。
A method for statistical analysis of two independent samples with respect to difference in location is investigated. The method uses the partial least squares projections to latent structures (PLS) with cross-validation. The relation to classical methods is discussed and a Monte Carlo study is performed to describe how the distribution of the test-statistic employed depends on the number of objects, the number of variables, the percentage variance explained by the first PLS-component and the percentage missing values. Polynomial approximations for the dependency of the 50 per cent and the 5 per cent levels of the test-statistic on these factors are given. The polynomial for the 50 per cent level is complicated, involving several first-, second- and third-degree terms, whereas the polynomial for the 5 per cent level is dependent only on the number of objects and the size of the first component. A separate Monte Carlo experiment indicates that a moderate difference in sample size does not affect the distribution of the test-statistic. The multi-sample location problem is also studied and the effect of increasing the number of samples on the test-statistic is shown in simulations.