Statistical Inference for High Dimensional Problems

Description

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.

Links & Downloads

1. Mukherjee, Rajarshi. 2014. Statistical Inference for High Dimensional Problems. Doctoral dissertation, Harvard University.
2. http://dissertations.umi.com/gsas.harvard:11516
3. http://nrs.harvard.edu/urn-3:HUL.InstRepos:12274550

Tags

Biostatistics

Minimax Estimation

Minimax Hypothesis Testing

Additional Fields

Identifer	oai:union.ndltd.org:harvard.edu/oai:dash.harvard.edu:1/12274550
Date	06 June 2014
Creators	Mukherjee, Rajarshi
Contributors	Lin, Xihong
Publisher	Harvard University
Source Sets	Harvard University
Language	en_US
Detected Language	English
Type	Thesis or Dissertation
Rights	open