estimate_qra_quantgen: Estimate qra model using quantgen package as backend

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

Estimate qra model using quantgen package as backend

Description

Estimate qra model using quantgen package as backend

Usage

estimate_qra_quantgen(
  qfm_train,
  y_train,
  qfm_test,
  intercept,
  constraint,
  quantile_groups,
  noncross = "constrain"
)

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
constraint	character specifying constraints on parameters; 'convex', 'positive' or 'unconstrained'
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
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.

Value

object of class qra_fit

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