作者pei16 (^^)
看板NCTU-STAT98G
标题[演讲公告] 1120 统计所专题演讲
时间Mon Nov 16 21:39:13 2009
交通大学、清华大学 统计学研究所 专题演讲
题 目:Correlation-Based Functional Clustering via Subspace Projection
主讲人:李百灵教授 (淡江大学统计系)
时 间:98年11月20日(星期五)上午10:40-11:30
(上午10:20-10:40茶会於交大统计所429室举行)
地 点:交大综合一馆427室
Abstract
A correlation-based functional clustering method is proposed for grouping
curves with similar shapes. A correlation between two random functions
defined through the functional inner product is used as similarity measure.
Curves with similar shapes are embedded in the cluster subspace spanned by a
mean shape function and eigenfunctions of the covariance kernel. The cluster
membership prediction for each curve attempts to maximize the functional
correlation between the observed and predicted curves via shape
standardization and subspace projection among all possible clusters. The
proposed method accounts for shape differentials through the functional
multiplicative random-effects shape function model for each cluster, which
regards random scales and intercept shifts as a nuisance. A consistent
estimate is proposed for the random scale effect, whose sample variance
estimate is also consistent. The derived identifiability conditions for the
clustering procedure unravel the predictability of cluster memberships.
Simulation studies and a real data example illustrate the proposed method.
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