We propose a MANOVA test for semicontinuous data that is applicable also when the dimensionality exceeds the sample size. The test statistic is obtained as a likelihood ratio, where numerator and denominator are computed at the maxima of penalized likelihood functions under each hypothesis. Closed form solutions for the regularized estimators allow us to avoid computational overheads. We derive the null distribution using a permutation scheme. The power and level of the resulting test are evaluated in a simulation study. We illustrate the new methodology with two original data analyses, one regarding microRNA expression in human blastocyst cultures, and another regarding alien plant species invasion in the island of Socotra (Yemen).

翻译：本文提出一种适用于半连续数据的MANOVA检验，该方法在维度超过样本量的情况下依然有效。检验统计量基于似然比构建，其中分子和分母分别在各假设下的惩罚似然函数最大值处计算。正则化估计量的闭式解避免了计算开销。我们通过置换方案推导了零分布，并通过模拟研究评估了检验的势和显著性水平。通过两项原始数据分析（一项涉及人类囊胚培养物中的microRNA表达，另一项涉及也门索科特拉岛的入侵外来植物物种），我们展示了新方法的实用性。