estimate_qra: Estimate Quantile Regression Averaging model

In reichlab/covidEnsembles: What the Package Does (One Line, Title Case)

Estimate Quantile Regression Averaging model

Description

Estimate Quantile Regression Averaging model

Usage

estimate_qra(
  qfm_train,
  y_train,
  qfm_test = NULL,
  intercept = FALSE,
  combine_method = c("ew", "convex", "positive", "unconstrained", "median"),
  quantile_groups = NULL,
  noncross = "constrain",
  backend = "optim",
  max_weight = NULL,
  partial_save_frequency,
  partial_save_filename,
  ...
)

Arguments

qfm_train	QuantileForecastMatrix with training set predictions
y_train	numeric vector of responses for training set
qfm_test	QuantileForecastMatrix with test set predictions
intercept	logical specifying whether an intercept is included
combine_method	character specifying the approach to model combination: "equal", "convex", "positive", "unconstrained", or "median". The first four form a linear combination of quantiles across component models with varying levels of restrictions on the combination coefficients. "median" takes the median across models at each quantile level.
quantile_groups	Vector of group labels for quantiles, having the same length as the number of quantiles. Common labels indicate that the ensemble weights for the corresponding quantile levels should be tied together. Default is rep(1,length(quantiles)), which means that a common set of ensemble weights should be used across all levels. This is the argument tau_groups for quantgen::quantile_ensemble, and may only be supplied if ⁠backend = 'quantgen⁠
noncross	string specifying approach to handling quantile noncrossing: one of "constrain" or "sort". "constrain" means estimation is done subject to constraints ruling out quantile crossing. "sort" means no such constraints are imposed during estimation, but the resulting forecasts are sorted.
backend	implementation used for estimation; currently either 'optim', using L-BFGS-B as provided by the optim function in R; 'NlcOptim', using NlcOptim::solnl; or 'quantgen', using quantgen::quantile_ensemble
max_weight	numeric value for maximum weight. Ignored unless qra_model is rel_wis_weighted_median or rel_wis_weighted mean and backend is grid_search

Value

object of class qra_fit

reichlab/covidEnsembles documentation built on Jan. 31, 2024, 7:21 p.m.