Statistics Theory and Methods

[1] Rerandomization Strategies for Balancing Covariates Using Pre-Experimental Longitudinal Data

Per Johansson Uppsala University and IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Mårten Schultzberg Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33005

Journal of Computational and Graphical Statistics, 29, (4), 798-813, 2020.5
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[2] Asymptotic Inference for Optimal Rerandomization Designs

Mårten Schultzberg Uppsala University, Sweden Per Johansson Uppsala University, Sweden; Tsinghua University, China

Statistics Theory and Methods mathscidoc:2206.33004

Open Statistics, 1, (1), 49-58, 2021.1
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[3] On optimal rerandomization designs

Per Johansson Uppsala University and IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Donald B. Rubin Tsinghua University, Beijing, China Mårten Schultzberg Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33003

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 83, (2), 395-403, 2021.4
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[4] Plug-in L2-upper error bounds in deconvolution, for a mixing density estimate in Rd and for its derivatives, via the L1-error for the mixture

Yannis G. Yatracos Yau Mathematical Sciences Center, Tsinghua University, Beijing, People's Republic of China; School of Communication and Media Studies, Cyprus University of Technology, Lemesos, Cyprus

Statistics Theory and Methods mathscidoc:2206.33002

Statistics, 53, (6), 1251-1268, 2019.7
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[5] Inference in Experiments Conditional on Observed Imbalances in Covariates

Per Johansson Department of Statistics, Uppsala University, Uppsala, Sweden; IFAU, Uppsala, Sweden; Tsinghua University, Beijing, China Mattias Nordin Department of Statistics, UCFS and Urban Lab, Uppsala University, Uppsala, Sweden

Statistics Theory and Methods mathscidoc:2206.33001

The American Statistician, 00, (0), 1-11, 2022.4
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