Print: Highly Adaptive Lasso Conditional Density Estimates
Usage
# S3 method for class 'haldensify'
print(x, ...)Value
None. Called for the side effect of printing an informative summary
of slots of objects of class haldensify.
Examples
# simulate data: W ~ U[-4, 4] and A|W ~ N(mu = W, sd = 0.5)
set.seed(11249)
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 = c(3, 5),
lambda_seq = exp(seq(-1, -15, length = 50L)),
max_degree = 2, smoothness_orders = 0, reduce_basis = 0.1
)
print(haldensify_fit)
#> HAL Conditional Density Estimation
#> Number of bins over support of A: 5
#> CV-selected lambda: 0.0038
#> Summary of fitted HAL:
#> coef term
#> <num> <char>
#> 1: 13.66335 (Intercept)
#> 2: -18.73701 [ I(W >= -2.086) ]
#> 3: -15.56878 [ I(W >= -1.105) ]
#> 4: 15.39282 [ I(W >= -1.612) ]
#> 5: 15.17157 [ I(bin_id >= 2) ]
#> 6: 13.70079 [ I(bin_id >= 3) ]
#> 7: -13.35268 [ I(W >= 1.006) ]
#> 8: 12.79074 [ I(bin_id >= 4) ]
#> 9: -11.35484 [ I(W >= 1.884) ]
#> 10: 11.30173 [ I(W >= 1.487) ]