Forecast glm models

This function uses fitted model object from glm_fit and future covariate data to create probablistic forecasts at specific quantiles derived from the "alpha" parameter.

Usage

glm_forecast(
  .data,
  new_covariates = NULL,
  fit,
  alpha = c(0.01, 0.025, seq(0.05, 0.45, by = 0.05)) * 2
)

Arguments

.data

Data including all explanatory and outcome variables needed for modeling

new_covariates

Tibble with one column per covariate, and n rows for n horizons being forecasted

fit

Fitted model object from glm_fit; note must be accessed from first element in "fit" column

alpha

Vector specifying the threshold(s) to be used for prediction intervals; alpha of 0.05 would correspond to 95% PI; default is c(0.01, 0.025, seq(0.05, 0.45, by = 0.05)) * 2 to create a range of intervals

Value

A tibble with forecasted data including the following columns:

• epiweek: The epidemiological week for the forecasted horizon

• epiyear: The epidemiological year for the forecasted horizon

• quantile: The quantile for the forecasted value; NA for point estimate

• value: The forecasted value