SUPPLEMENT TO “A SIMPLE BOOTSTRAP METHOD FOR CONSTRUCTING NONPARAMETRIC CONFIDENCE BANDS FOR FUNCTIONS.”

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Local Linear Forests (2018, methodology): “Developing methods for random forest inference that do not rely on undersmoothing following, for example, Hall and Horowitz (2013), would be of considerable interest; however, this falls beyond the scope of the present article.”
Bootstrap Methods in Econometrics (2018, unknown): “Hall and Horowitz (2013) (HH) and Horowitz and Krishnamurthy (2018) (HK) describe bootstrap methods for overcoming this problem in models (5.1) and (5.2), respectively.”
Doubly robust uniform confidence band for the conditional average treatment effect function (2016, background): “For example, Ogburn, Rotnitzky, and Robins (2015) consider a similar issue in the context of the local average treatment effect (LATE) of Imbens and Angrist (1994). Ogburn, Rotnitzky, and Robins (2015) emphasize that conditioning on a large number of covariates Z may be required to make it plausible”
Simple and honest confidence intervals in nonparametric regression (2016, background): “For example, in the context of constructing confidence bands for a regression function f(x), Hall and Horowitz (2013) propose bands that have an average coverage property in that the bands achieve coverage of f(x) for a random subset of values of x.”