Modelling SARS data using threshold geometric process

Jennifer S. K. CHAN, Leung Ho Philip YU, Yeh LAM, Alvin P. K. HO

Research output: Contribution to journalArticlespeer-review

23 Citations (Scopus)

Abstract

During the outbreak of an epidemic disease, for example, the severe acute respiratory syndrome (SARS), the number of daily infected cases often exhibit multiple trends: monotone increasing during the growing stage, stationary during the stabilized stage and then decreasing during the declining stage. Lam first proposed modelling a monotone trend by a geometric process (GP) {Xi, i=1,2,…} directly such that {ai−1Xi, i=1,2,…} forms a renewal process for some ratio a>0 which measures the direction and strength of the trend. Parameters can be conveniently estimated using the LSE methods. Previous GP models limit to data with only a single trend. For data with multiple trends, we propose a moving window technique to locate the turning point(s). The threshold GP model is fitted to the SARS data from four regions in 2003. Copyright © 2005 John Wiley & Sons, Ltd.
Original languageEnglish
Pages (from-to)1826-1839
JournalStatistics in Medicine
Volume25
Issue number11
Early online dateDec 2005
DOIs
Publication statusPublished - Jun 2006

Citation

Chan, J. S. K., Yu, P. L. H., Lam, Y., & Ho, A. P. K. (2006). Modelling SARS data using threshold geometric process. Statistics in Medicine, 25(11), 1826-1839. doi: 10.1002/sim.2376

Keywords

  • Geometric process
  • Monotone trend
  • Threshold model
  • Non-parametric method
  • Moving window
  • Turning points

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