Mathematics

[341] 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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[342] 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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[343] Rerandomization: A complement or substitute for stratification in randomized experiments?

Per Johansson Department of Statistics, Uppsala university, Sweden Mårten Schultzberg Department of Statistics, Uppsala university, Sweden

TBD mathscidoc:2206.43023

Journal of Statistical Planning and Inference, 218, 43-58, 2022.5
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[344] Study protocol for a comparative effectiveness evaluation of abiraterone acetate against enzalutamide: a longitudinal study based on Swedish administrative registers

Per Johansson Statistics, Uppsala University, Uppsala, Sweden; YMSC, Tsinghua University, Beijing, China Paulina Jonéus Department of Statistics, Uppsala University, Uppsala, Sweden Sophie Langenskiöld Department of Medical Sciences, Uppsala University, Uppsala, Sweden

TBD mathscidoc:2206.43022

BMJ Open 2021, 11, 2021.10
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[345] Residual’s influence index (RINFIN), bad leverage and unmasking in high dimensional L2-regression

Yannis G. Yatracos Yau Mathematical Sciences Center, Tsinghua University, Beijing, China; Beijing Institute of Mathematical Sciences and Applications, Beijing, China

Statistics Theory and Methods,Data Analysis mathscidoc:2206.86001

Statistics Analysis and Data Mining, 15, (1), 125-138, 2021.9
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