get_log_scores_via_direct_simulation: Get log scores and full predictive distributions for each...

In reichlab/adaptively-weighted-ensemble: Adaptively Weighted Ensembles via Stacking

Description

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.

Usage

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)

Arguments

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

Value

none

reichlab/adaptively-weighted-ensemble documentation built on May 27, 2019, 4:53 a.m.