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 personalized treatments. In this paper, we discuss general approach to estimating such quantities: begin with simple plug-in estimator based on an estimate function, then corre...

The discovery t ha t the minimax decision rule performs poorly in some games has sparked interest in possible al ternatives to minimax. Until recently, the only games in which minimax was known to perform poorly were games which were mainly of theoretical interest. However, this paper reports results showing poor performance of minimax in a more common game called kalah. For the kalah games tes...

this paper is concerned with the problem of finding the minimax estimators of the scale parameter ? in a family of transformed chi-square distributions, under asymmetric squared log error (sle) and modified linear exponential (mlinex) loss functions, using the lehmann theorem [2]. also we show that the results of podder et al. [4] for pareto distribution are a special case of our results for th...

This paper describes comparisons of the minimax backup rule and the product back-up rule on a wide variety of games, including P-games, G-games, three-hole kalah, Othello, and Ballard’s incremental game. In three-hole kalah, the product rule plays better than a minimax search to the same depth. This is a remarkable result, since it is the first widely known game in which product has been found ...

The authors propose and explore new regression designs. Within a particular parametric class, these designs are minimax robust against bias caused by model misspecification while attaining reasonable levels of efficiency as well. The introduction of this restricted class of designs is motivated by a desire to avoid the mathematical and numerical intractability found in the unrestricted minimax ...