Items where department is "Statistics"

University Structure (106352) LSE (106352) Academic Departments (62972) Statistics (1721)
Number of items: 9.
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  • Chen, Xuanyu, Zhu, Jin, Zhu, Junxian, Wang, Xueqin, Zhang, Heping (2026). Reconstruct Ising Model with global optimality via SLIDE. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2025.2571245
    • Public
  • Cen, Zetai, Chen, Yudong, Lam, Clifford (2026). Inference on dynamic spatial autoregressive models with change point detection. Journal of Business and Economic Statistics, https://doi.org/10.1080/07350015.2025.2572768
  • Leocata, Marta, Livieri, Giulia, Morlacchi, Silvia, Corvino, Fausto, Flandoli, Franco, Pirni, Alberto Eugenio Ermenegildo (2026). Understanding the householder solar panel consumer: a Markovian model and its societal implications. Technological Forecasting and Social Change, 225, https://doi.org/10.1016/j.techfore.2026.124555
  • Li, Mengchu, Chen, Yudong, Wang, Tengyao, Yi, Yu (2026). Robust mean change point testing in high-dimensional data with heavy tails. IEEE Transactions on Information Theory, 72(1), 571 - 609. https://doi.org/10.1109/TIT.2025.3634207 picture_as_pdf
    • Restricted
  • Gao, Fengnan, Wang, Tengyao (2026). Detecting sparse change in regression coefficients in the presence of dense nuisance parameters. Information and Inference: A Journal of the IMA, [In Press] picture_as_pdf
  • Ma, Tao, Zhu, Jin, Cai, Hengrui, Qi, Zhengling, Chen, Yunxiao, Shi, Chengchun, Laber, Eric B. (2026). Sequential knockoffs for variable selection in reinforcement learning. Journal of the American Statistical Association, [In Press] picture_as_pdf
  • Qiao, Jiawei, Chen, Yunxiao, Ying, Zhiliang (2026). Exploratory hierarchical factor analysis with an application to psychological measurement. Statistica Sinica, [In Press] picture_as_pdf
  • Sterzinger, Philipp, Kosmidis, Ioannis, Moustaki, Irini (2026). Maximum softly penalised likelihood in factor analysis. Psychometrika, [In Press] picture_as_pdf
  • Wang, Tengyao (2026). Proposer of the vote of thanks to Whiteley et al. and contribution to the Discussion of ‘Statistical exploration of the Manifold Hypothesis’. Journal of the Royal Statistical Society. Series B: Statistical Methodology, https://doi.org/10.1093/jrsssb/qkag002 [In Press] picture_as_pdf