Multivariate Modality Inference Using Gaussian Kernel
2014; Scientific Research Publishing; Volume: 04; Issue: 05 Linguagem: Inglês
10.4236/ojs.2014.45041
ISSN2161-7198
Autores Tópico(s)Gene expression and cancer classification
ResumoThe 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.
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