A new algorithm for segmenting data from time series

Author

Duncan, Stephen R. ; Bryant, Greyham F.

Author_Institution

Control Syst. Centre, Univ. of Manchester Inst. of Sci. & Technol., UK

Volume

3

fYear

1996

fDate

11-13 Dec 1996

Firstpage

3123

Abstract

This paper addresses the problem of dividing a time series into segments, where the data in each segment, is generated by a different underlying linear model. The technique is used to identify changes in the process generating the data. The identification of changes is recast as a shortest path problem which is solved using dynamic programming. The algorithm determines the total number of jumps within the data, the location of these jumps and the order of the model within each segment. Results of the application of the algorithm to the analysis of retail sales data are presented

Keywords

dynamic programming; graph theory; least squares approximations; marketing; minimisation; retailing; time series; data segmentation; dynamic programming; linear model; retail sales data; shortest path problem; time series; Control systems; Educational institutions; Least squares methods; Marketing and sales; Medical control systems; Shortest path problem; Supply chain management; Supply chains; Systems engineering and theory; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.573607

Filename

573607