regressAR: Combines multiple autoregressive models into one prediction...

In olshena/COVIDNearTerm: Near Term Prediction of COVID-Related Population Metrics

Combines multiple autoregressive models into one prediction model using a least sqares regression model

Description

Need to fill in description data

Usage

regressAR(
  vec,
  x = NULL,
  output_type = "max",
  wsize = 14,
  method = c("equal", "unweighted", "triangle"),
  pdays = 28,
  nsim = 100,
  skip = 0,
  seed = NULL,
  regression_weights = NULL,
  rhat_method = c("none", "geometric", "arithmetic"),
  debug = FALSE
)

Arguments

vec	A vector of numeric data, will also be include as a default predictor
x	A data frame containing covariates with which to generate predictive model, if unspecified, defaults to vec
output_type	A string indicating which outcome measure should be predicted. Must be one of Min, FirstQu, Median, Mean, ThirdQu, or Max
wsize	Number of prior observations to use for averaging, default is 14
method	Type of weighting to use in individual prediction models, default is equal
pdays	Number of days into the future to make predictions, default is 28
nsim	Number of simulations, default is 100
skip	Number of input values to skip, default is 0
seed	Seed for random number generator
regression_weights	An array specifying regression weights. Currently not implemented
rhat_method	Method for calculating rhat, if "none", rhat = 1 and has no effect
debug	TRUE returns buildAR objects in addition to standard output

Value

A list containing the specified output statistics for each sim

olshena/COVIDNearTerm documentation built on May 27, 2023, 1:23 p.m.