predict.quantile_baseline: Predict future disease incidence by resampling one-step-ahead...

In reichlab/simplets: Simple models for time series forecasting

Predict future disease incidence by resampling one-step-ahead forecasts

Description

Predict future disease incidence by resampling one-step-ahead forecasts

Usage

## S3 method for class 'quantile_baseline'
predict(
  quantile_baseline,
  newdata,
  quantiles,
  horizon,
  nsim,
  origin = c("obs", "loess", "median"),
  n_origin = 7,
  force_nonneg = FALSE
)

Arguments

quantile_baseline	a quantile_baseline fit object
newdata	numeric vector of length at least one with incident counts
quantiles	quantile levels for which to generate predictions
horizon	number of time steps forward to predict
nsim	number of samples to use for generating predictions at horizons greater than 1
origin	string specifying whether to project forward from the most recent observation ("obs"), from the fitted value from a LOESS smooth ("loess") based on a window of size ⁠n_origin``, or from the median of the last ⁠n_origin⁠ observed values (⁠"median"')
n_origin	number of data points used in a window for a LOESS fit or for calculating the median. Defaults to 7, which seems reasonable for daily data.
force_nonneg	boolean; if TRUE, results are forced to be non-negative
cum_data	numeric vector of length at least one with cumulative counts

Value

matrix of samples of incidence

reichlab/simplets documentation built on Sept. 16, 2024, 10:24 p.m.