print.GATES_info

An object of the class <code>"GATES_info"</code>, as returned by the function <code><a rd-options="" href="/link/get_GATES?package=GenericML&version=0.2.2" data-mini-rdoc="GenericML::get_GATES">get_GATES</a>()</code>.

digits

Additional arguments to be passed down.

Print method for a <code>"GATES_info"</code> object

Generic Machine Learning Inference on heterogeneous treatment effects in randomized experiments as proposed in Chernozhukov, Demirer, Duflo and Fern<c3><a1>ndez-Val (2020) <arXiv:1712.04802>. This package's workhorse is the 'mlr3' framework of Lang et al. (2019) <doi:10.21105/joss.01903>, which enables the specification of a wide variety of machine learners. The main functionality, GenericML(), runs Algorithm 1 in Chernozhukov, Demirer, Duflo and Fern<c3><a1>ndez-Val (2020) <arXiv:1712.04802> for a suite of user-specified machine learners. All steps in the algorithm are customizable via setup functions. Methods for printing and plotting are available for objects returned by GenericML(). Parallel computing is supported.

Max Welz

GenericML

Generic Machine Learning Inference

Andreas Alfons

Mert Demirer

Victor Chernozhukov

print.GATES_info function

An object of the class <code>"GATES_info"</code>, as returned by the function <code><a rd-options='' href='get_GATES'>get_GATES</a>()</code>.

print.GATES_info: Print method for a `"GATES_info"` object

Description

Usage

Arguments

Value