S-Space College of Natural Sciences (자연과학대학) Dept. of Statistics (통계학과) Theses (Master's Degree_통계학과)
A review on Clustering Methods for Functional Data
함수열 자료의 군집방법에 대한 연구
- 자연과학대학 통계학과
- Issue Date
- 서울대학교 대학원
- 학위논문 (석사)-- 서울대학교 대학원 : 통계학과, 2015. 2. 박병욱.
- Many studies have been done for clustering functional data as considerable functional data are obtained recently. We reviewed overall approaches for clustering functional data proposed so far. Those approaches consist of a nonparametric approach which uses dissimilarity between curves as dissimilarity measure, a filtering and clustering technique which is simple and intuitive and a model-based clustering method which assumes a probability distribution of finite dimensional coefficients estimated from data. Model-based methods are reviewed in detail, particularly. Also, we provided an application to energy data using model-based models for functional data to illustrate model-based methods with specific basis.