tmp_method.CC_LS

<p>Temporary fix for convex combination method mean squared error
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another</p>

Targeted minimum loss-based estimators of counterfactual means and
causal effects that are doubly-robust with respect both to consistency and
asymptotic normality (Benkeser et al (2017), <doi:10.1093/biomet/asx053>; MJ
van der Laan (2014), <doi:10.1515/ijb-2012-0038>).

David Benkeser

drtmle

Doubly-Robust Nonparametric Estimation and Inference

Nima Hejazi

tmp_method.CC_LS function

Temporary fix for convex combination method mean squared error
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another — tmp_method.CC_LS

Temporary fix for convex combination method mean squared error
Relative to existing implementation, we reduce the tolerance at which
we declare predictions from a given algorithm the same as another

tmp_method.CC_LS: Temporary fix for convex combination method mean squared error Relative to existing implementation, we reduce the tolerance at which we declare predictions from a given algorithm the same as another

Description

Usage

Arguments