This performs similarly to Serfling models, except fit is done with an ARIMA approach.
flurima()
data | A dataframe class object, must contain time variable, epidemic indicator, and measure of influenza morbidity |
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outc | an unquoted name of a column in data which corresponds to the outcome variable of interest |
time | an unquoted name of a column in data object, must be a numeric/integer class variable in dataframe which corresponds to a unit of time, must be unique (i.e. non-repeating) |
season | Either 'T', where the epidemic baseline model will be created assuming time variable is a date, and Oct-May is epidemic season, or the name of a column which is a logical vector flagging a given week as epidemic or not |
order | A vector of length three, given ARIMA(p,d,q) specifications. |
seasonal | A vector of length three, given ARIMA(p,d,q) specifications. |
echo | A logical, if T will print variables used in model. |
... | other options passed on to ARIMA model |
an object of class data.frame, fit, upper and lower confidence bounds