quantile_reg: Quantile regression

In cmu-delphi/epipredict: Basic epidemiology forecasting methods

Quantile regression

Description

quantile_reg() generates a quantile regression model specification for the tidymodels framework. Currently, the only supported engines are "rq", which uses quantreg::rq(). Quantile regression is also possible by combining parsnip::rand_forest() with the grf engine. See grf_quantiles.

Usage

quantile_reg(
  mode = "regression",
  engine = "rq",
  quantile_levels = c(0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95),
  method = "br"
)

Arguments

mode	A single character string for the type of model. The only possible value for this model is "regression".
engine	Character string naming the fitting function. Currently, only "rq" and "grf" are supported.
quantile_levels	A scalar or vector of values in (0, 1) to determine which quantiles to estimate (default is the set 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95).
method	A fitting method used by quantreg::rq(). See the documentation for a list of options.

See Also

fit.model_spec(), set_engine()

Examples

library(quantreg)
tib <- data.frame(y = rnorm(100), x1 = rnorm(100), x2 = rnorm(100))
rq_spec <- quantile_reg(quantile_levels = c(.2, .8)) %>% set_engine("rq")
ff <- rq_spec %>% fit(y ~ ., data = tib)
predict(ff, new_data = tib)

cmu-delphi/epipredict documentation built on March 5, 2025, 12:17 p.m.