Liu, Lin, Mukherjee, Rajarshi, and Robins, James M. On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning. Retrieved from https://par.nsf.gov/biblio/10223339. Statistical Science 35.3 Web. doi:10.1214/20-STS786.

Liu, Lin, Mukherjee, Rajarshi, & Robins, James M. On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning. Statistical Science, 35 (3). Retrieved from https://par.nsf.gov/biblio/10223339. https://doi.org/10.1214/20-STS786

Liu, Lin, Mukherjee, Rajarshi, and Robins, James M. "On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning". Statistical Science 35 (3). Country unknown/Code not available. https://doi.org/10.1214/20-STS786. https://par.nsf.gov/biblio/10223339.

@article{osti_10223339,
place = {Country unknown/Code not available}, title = {On Nearly Assumption-Free Tests of Nominal Confidence Interval Coverage for Causal Parameters Estimated by Machine Learning}, url = {https://par.nsf.gov/biblio/10223339}, DOI = {10.1214/20-STS786}, abstractNote = {}, journal = {Statistical Science}, volume = {35}, number = {3}, author = {Liu, Lin and Mukherjee, Rajarshi and Robins, James M.}, editor = {null} }