learnDevMu

The  <code>matrix</code>  of  observations,  see  for  instance  the  <code>obs</code>
argument of the <code>function</code> <code>tmle.npvi</code>.

The <code>vector</code>  <code>effIC1</code> of the  first component of  the efficient
influence curve, as currently estimated, evaluated at our observations.

effIC1

The  <code>vector</code> <code>muW</code>  of the  conditional expectation  of $X$
given $W$, as currently estimated, evaluated at our observations.

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

Prescribes the amount of information  output by the function.  Defaults to
<code>FALSE</code>.

verbose

Function   for  the   estimation   of  the   conditional  expectation   of
<code>(X-muW)*effIC1</code>   given  $W$  when   <code>flavor</code>  is   set  to
"learning".

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.

learnDevMu: Estimation of Cond. Expect. of (X-muW)*effIC1 Given W

Description

Arguments

Value

See Also