TY - JOUR
T1 - 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
AU - Soyiri, Ireneous Ngmenlanaa
AU - Reidpath, Daniel
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
UR - http://www.plosone.org/article/fetchObject.action?uri=info%3Adoi%2F10.1371%2Fjournal.pone.0078215&representation=PDF
U2 - 10.1371/journal.pone.0078215
DO - 10.1371/journal.pone.0078215
M3 - Article
SN - 1932-6203
VL - 8
JO - PLoS ONE
JF - PLoS ONE
IS - 10
M1 - e78215
ER -