flunnet: flunnet: Estimating attributable mortality with Neural...

In kmcconeghy/flumodelr: An R Package for Estimating Attributable Influenza Morbidity and Mortality

Description

Estimates fitted curves and baseline using the nnetar function in the forecast package. This is a Feed-forward neural network with a single hidden layer and lagged inputs for forecasting univariate time series.

Usage

flunnet()

Arguments

data	A dataframe class object, must contain time variable, epidemic indicator, and measure of influenza morbidity
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
echo	A logical, if T will print variables used in model.
...	other options passed on to nnetar()

Value

an object of class data.frame, fit, upper and lower confidence bounds

kmcconeghy/flumodelr documentation built on June 7, 2019, 8:47 p.m.