no code implementations • 12 Jun 2020 • Jeremy R. Coyle, Nima S. Hejazi, Ivana Malenica, Rachael V. Phillips, Benjamin F. Arnold, Andrew Mertens, Jade Benjamin-Chung, Weixin Cai, Sonali Dayal, John M. Colford Jr., Alan E. Hubbard, Mark J. Van Der Laan
Targeted Learning is a subfield of statistics that unifies advances in causal inference, machine learning and statistical theory to help answer scientifically impactful questions with statistical confidence.
1 code implementation • 16 Oct 2017 • Nima S. Hejazi, Sara Kherad-Pajouh, Mark J. Van Der Laan, Alan E. Hubbard
The widespread availability of high-dimensional biological data has made the simultaneous screening of many biological characteristics a central problem in computational biology and allied sciences.
Methodology
1 code implementation • 24 Apr 2017 • Weixin Cai, Nima S. Hejazi, Alan E. Hubbard
Current statistical inference problems in areas like astronomy, genomics, and marketing routinely involve the simultaneous testing of thousands -- even millions -- of null hypotheses.