Statistical Inference for High Dimensional Problems

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Statistical Inference for High Dimensional Problems

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Title: Statistical Inference for High Dimensional Problems
Author: Mukherjee, Rajarshi
Citation: Mukherjee, Rajarshi. 2014. Statistical Inference for High Dimensional Problems. Doctoral dissertation, Harvard University.
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Abstract: In this dissertation, we study minimax hypothesis testing in high-dimensional regression against sparse alternatives and minimax estimation of average treatment effect in an semiparametric regression with possibly large number of covariates.
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:12274550
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