Multivariate Modality Inference Using Gaussian Kernel

• 作者: Surajit Ray Yansong Cheng
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: MODALITY KERNEL Density ESTIMATE Mode CLUSTERING
• 年，卷（期）: 2014,（5）
• 页码范围: 419-434
• 页数: 16页
• 分类号: O1

摘要

The number of modes (also known as modality) of a kernel density estimator (KDE) draws lots of interests and is important in practice. In this paper, we develop an inference framework on the modality of a KDE under multivariate setting using Gaussian kernel. We applied the modal clustering method proposed by [1] for mode hunting. A test statistic and its asymptotic distribution are derived to assess the significance of each mode. The inference procedure is applied on both simulated and real data sets.