Description Usage Arguments Value
for a given season using a predictive method that works by directly simulating predictive distributions of each target. Results are stored in a data frame, saved in a .rds file with a name like "model_name-region-season-loso-predictions.rds" Results have columns indicating the analysis time season and season week, model name, log scores for each prediction target, the "log score" used in the competition (adding probabilities from adjacent bins) for each prediction target, as well as the log of the probability assigned to each bin.
1 2 3 4 | get_log_scores_via_direct_simulation(analysis_time_season,
first_analysis_time_season_week = 10, last_analysis_time_season_week = 41,
region, prediction_target_var, incidence_bins, incidence_bin_names, n_sims,
model_name, fits_path, prediction_save_path)
|
analysis_time_season |
character vector of length 1 specifying the season to obtain predictions for, in the format "2000/2001" |
first_analysis_time_season_week |
integer specifying the first week of the season in which to make predictions, using all data up to and including that week to make predictions for each following week in the season |
last_analysis_time_season_week |
integer specifying the last week of the season in which to make predictions, using all data up to and including that week to make predictions for each following week in the season |
region |
string specifying the region to use, in the format "X" or "Region k" where k in 1, ..., 10 |
prediction_target_var |
string specifying the name of the variable in data for which we want to make predictions |
incidence_bins |
a data frame with variables lower and upper defining lower and upper endpoints to use in binning incidence |
incidence_bin_names |
a character vector with a name for each incidence bin |
n_sims |
integer number of samples to simulate |
model_name |
name of model, stored in the results data frame |
fits_path |
path to directory where fitted models are stored |
prediction_save_path |
path to directory where results will be saved |
none
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