predict_density: Helper function to predict from a super learner fit on the...
In benkeser/intermed:

Helper function to predict from a super learner fit on the hazard scale to obtain a prediction on the density scale

predict_density(
  sl_fit_conditional,
  sl_fit_marginal,
  how_predict,
  all_mediator_values,
  a_val,
  validC,
  M1,
  M2,
  valid_n,
  stratify
)

`sl_fit_conditional`	A fitted SuperLearner object for the M1 \| M2, C, A regression
`sl_fit_marginal`	A fitted SuperLearner object for the M2 \| C, A regression
`how_predict`	Needed to figure out how to predict from model. Possible choices are "SuperLearner", "single_algo", and "glm"
`all_mediator_values`	data.frame of all observed mediator values
`a_val`	Relevant treatment level
`validC`	Confounders in the validation set
`M1`	All M1 values
`M2`	All M2 values
`valid_n`	Number of obs in validation set
`stratify`	Were sl_fit's stratified?