predcurves: Predict hospitalization curves based on observed seasons
In jrgant/FluHospPrediction: Code for Flu Hospital Prediction Paper

predict_curves

R Documentation

Predict hospitalization curves based on observed seasons

Predict hospitalization curves based on observed seasons

predict_curves(
  hosp_obs,
  tf_list,
  cv_list,
  lambda_type = c("lambda.min", "lambda.1se")
)

`hosp_obs`	A list containing the hospitalization rate data frames. One dataset per list item.
`tf_list`	A list containing trend filter fits to observed seasons. One fit per list item.
`cv_list`	List. containing cross-validation output for each season's trendfilter fit.
`lambda_type`	Character. One of "lambda.min" or "lambda.1se", each corresponding to different criteria used to select the lambda penalty for each trendfilter fit. Per the `genlasso` package documentation, "lambda.min" is the lambda that minimizes the cross-validated error (average error across folds), while "lambda.1se" selects the largest lambda value that produces a cross-validated error within one standard deviation of the minimum cross-validated error.