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Statistics Department Seminar presents "Augmented minimax linear estimation"

Augmented minimax linear estimation
Tuesday, August 6, 2019 - 4:30pm
Sloan Mathematics Center, Room 380C
David Hirshberg (Stanford GSB)
Abstract / Description: 

Many statistical estimands can expressed as continuous linear functionals of a conditional expectation function. This includes the average treatment effect under unconfoundedness and generalizations for continuous-valued and personalized treatments. In this talk, we discuss a general approach to estimating such quantities: we begin with a simple plug-in estimator based on an estimate of the conditional expectation function, and then correct the plug-in estimator by subtracting a minimax linear estimate of its error. We show that our method is semiparametrically efficient under weak conditions and observe promising performance on both real and simulated data.