Conditional Density Estimation with Heteroskedasticity

TODO: The following code has a bug / statistical issue. =======================================================

Usage

lnr_heteroskedastic_density(
  data,
  formula,
  mean_lnr,
  var_lnr,
  mean_lnr_args = NULL,
  var_lnr_args = NULL,
  density_args = NULL
)

Details

I think there are bugs with this because performing a basic test that if we fix the conditioning set (X) and integrate, integrating a conditional probability density with X fixed should yield 1.

In numerical tests, when the variance is scaled for, integrating conditional densities seems to yield integration values exceeding 1 (sometimes by a lot). I am pretty sure this poses a problem for optimizing negative log likelihood loss.

Said numerical tests are displayed in the `Density-Estimation` article.