learnMuAux

The  <code>matrix</code>  of  observations,  see  for  instance  the  <code>obs</code>
argument of the  <code>function</code> <code>tmle.npvi</code>, where only observations
with $X\neq 0$ are kept.

A  <code>logical</code>,  kept  for   compatibility,  which  should  be  set  to
<code>TRUE</code> (its default value). This requires that the result of each fit
be reduced  in size (for  a faster execution). Currently  implemented only
for flavor <code>learning</code>.

light

Function  for the  estimation of  the conditional  expectation  of $X$
given $(X\neq x_0, W)$, version based on 'glm'.

Targeted minimum loss estimation (TMLE) of a non-parametric variable importance measure of a continuous exposure 'X' on an outcome 'Y', taking baseline covariates 'W' into account.

learnMuAux: Estimation of Cond. Expect. of X Given (X!=x_0, W)

Description

Arguments

Value

See Also