A binary tree algorithm on change points detection

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51848

Title:	A binary tree algorithm on change points detection
Authors:	Fan,TH;Hsieh,HJ;Lee,HH
Contributors:	統計研究所
Keywords:	REGRESSION-MODELS;RANDOM-VARIABLES;SEQUENCE;NUMBER;TESTS
Date:	2011
Issue Date:	2012-03-27 19:07:36 (UTC+8)
Publisher:	國立中央大學
Abstract:	In this paper, an algorithm using binary trees is developed to detect the change points of a data set in which the data are assumed to be normally distributed. Usual BIC-type criteria are considered in the binary searching procedures when the number of change points is unknown. The algorithm is also extended to the switching regression models. Simulation study confirms that our algorithm is efficient compared with the ML-method. A real data example also verifies that the proposed procedure is appropriate.
Relation:	QUALITY & QUANTITY
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

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