models_lags: Fits the models to training data and generates the...

In khelmsmith/flm_NE_WNV: Functional Linear Modeling For Vector-borne Disease

Fits the models to training data and generates the predictions

Description

Fits the models to training data and generates the predictions

Usage

models_lags(
  allmods,
  allLagsT,
  allLagsO,
  fillzeros,
  allunits,
  nsim,
  predict_from = c("best", "all")
)

Arguments

allmods	List of models
allLagsT	Training data
allLagsO	Out-of-sample data
fillzeros	Logical. If TRUE fill in with zeros counties that have no cases ever.
allunits	Character. Vector of county names in complete data set. Used when fillzeros == TRUE
nsim	Integer. Number of samples to draw from posterior distribution. Defaults to zero, which has the expected value of cases in predcases.
predict_from	Character. predict from AIC best model only, or from all models?

Value

Returns predictions for the out-of-sample year, a list of fitted models, AIC scores, and the model with the lowest AIC score. The predictions object could be a vector (nsim = 0 and predict_from == "best"), a matrix (nsim > 0 and predict_from == "best"), or a list of vectors or matrices (predict_from == "all")

khelmsmith/flm_NE_WNV documentation built on June 24, 2022, 11:13 p.m.