The use of quantile regression to forecast higher than expected respiratory deaths in a daily time series: a study of New York city data 1987-2000

Ireneous Ngmenlanaa Soyiri, Daniel Reidpath

    Research output: Contribution to journalArticleResearchpeer-review

    4 Citations (Scopus)


    Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths.
    Original languageEnglish
    Article numbere78215
    Number of pages6
    JournalPLoS ONE
    Issue number10
    Publication statusPublished - 2013

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