learnDevTheta: Estimation of Cond. Expect. of (Y-thetaXW)^2 Given (X,W)

In tmle.npvi: Targeted Learning of a NP Importance of a Continuous Exposure

Description

Function for the estimation of the conditional expectation of (Y-thetaXW)^2 given (X,W) when flavor is set to "learning".

Arguments

obs	The matrix of observations, see for instance the obs argument of the function tmle.npvi.
thetaXW	The vector thetaXW of the conditional expectation of Y given (X,W), as currently estimated, evaluated at our observations.
light	A logical, kept for compatibility, which should be set to TRUE (its default value). This requires that the result of each fit be reduced in size (for a faster execution). Currently implemented only for flavor learning.
verbose	Prescribes the amount of information output by the function. Defaults to FALSE.
...	Additional arguments possibly needed.

Value

Returns the fitted object.

Author(s)

Antoine Chambaz, Pierre Neuvial

See Also

learnG, learnMuAux, learnTheta, learnCondExpX2givenW, learnCondExpXYgivenW, learnDevG, learnDevMu

tmle.npvi documentation built on May 1, 2019, 6:50 p.m.