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Title: Discrepancy Analysis of Activity Sequences: What Explains the Complexity of People’s Daily Activity–Travel Patterns?
Accession Number: 01518916
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: Sequence alignment, also known as optimal matching, has recently received new attention for use in analysis of activity patterns. The method is almost always combined with a data reduction technique, such as clustering analysis. The cluster-based approach is powerful for discovery of a typology of activity patterns of people. However, the use of the combination of the sequence alignment and cluster analysis methodologies does not seem to be successful for the identification of diverse factors that would affect activity sequence patterns. This outcome is because the loss of too much information may occur when the set of activity sequences is reduced to a small number of clusters. This paper proposes the use of a new combination of the sequence alignment and discrepancy analysis methodologies instead of the cluster-based approach. As a generalization of the principle of analysis of variance, discrepancy analysis allows the association between activity sequences characterized by a pairwise distance matrix and one or more covariates to be evaluated. In addition, an induction tree complements the sequence discrepancy analysis and displays how individual activity sequences vary with the value of covariates.
Monograph Title: Monograph Accession #: 01537243
Report/Paper Numbers: 14-4334
Language: English
Authors: Kim, KihongPagination: pp 24–33
Publication Date: 2014
ISBN: 9780309295123
Media Type: Print
Features: Figures
(2)
; References
(27)
; Tables
(4)
TRT Terms: Subject Areas: Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning
Files: TRIS, TRB, ATRI
Created Date: Jan 27 2014 3:30PM
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