Plot Method for HAL Conditional Density Estimates

# S3 method for haldensify
plot(x, ..., type = c("risk", "density"))

Arguments

x: Object of class haldensify, containing conditional density estimates, as produced by haldensify.
...: Additional arguments to be passed plot, currently ignored.
type: A character indicating the type of plot to be produced. Options include visualizing the empirical risks of the conditional density estimators across a grid of values of the regularization parameter and a plot of the estimated conditional density (based on the estimator selected by cross-validation). The latter has yet to be implemented.

Value

Object of class ggplot containing a plot of the desired

type.

Examples

# simulate data: W ~ U[-4, 4] and A|W ~ N(mu = W, sd = 0.5)
n_train <- 50
w <- runif(n_train, -4, 4)
a <- rnorm(n_train, w, 0.5)
# learn relationship A|W using HAL-based density estimation procedure
haldensify_fit <- haldensify(
  A = a, W = w, n_bins = 3,
  lambda_seq = exp(seq(-1, -10, length = 50)),
  # the following arguments are passed to hal9001::fit_hal()
  max_degree = 3, reduce_basis = 0.1
)
#> Warning: Some fit_control arguments are neither default nor glmnet/cv.glmnet arguments: n_folds; 
#> They will be removed from fit_control
plot(haldensify_fit)