对于高维度介质的有限样本t测试.
1Department of Mathematical Sciences, Kent State University, Kent, OH 44242, USA.
概括
新的统计测试准确地控制了小样本大小的高维数据的I型错误率. 这些非参数方法适用于正常或重尾数据,与传统的非对称测试不同.
科学领域:
- 统计 统计 统计 统计
- 统计推理 统计推理
- 高维数据分析 高维数据分析
背景情况:
- 当样本大小小时,非对称的统计测试难以准确的I型错误率.
- 传统方法需要不同的样本大小,限制它们在数据有限的领域的应用.
研究的目的:
- 开发新的统计测试,用于高维设置中的平均向量,采用非常小的样本大小.
- 在这些具有挑战性的条件下建立测试,以保持准确的I型错误率.
主要方法:
- 建议对平均向量进行单样,双样和ANOVA测试.
- 已确立的对拟议的统计数据的非对称分布,只需要不同的维度和固定的小样本大小 (≥3).
- 开发了适用于正常分布和重尾数据的非参数测试.
主要成果:
- 拟议的测试在各种样本大小和数据维度中保持了准确的I型错误率.
- 理论结果通过模拟研究得到证实.
- 在fMRI数据集上展示了实际应用.
结论:
- 开发的非参数测试为使用高维,小样本数据进行假设测试提供了强大的解决方案.
- 这些方法克服了传统非对称测试的局限性,扩大了它们的适用性.
- 这些测试在以前被认为是难以解决的场景中提供了可靠的推断.
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