References in zbMATH (referenced in 53 articles , 1 standard article )

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  1. Foygel Barber, Rina; Samworth, Richard J.: Local continuity of log-concave projection, with applications to estimation under model misspecification (2021)
  2. Nelson, Barry L.; Wan, Alan T. K.; Zou, Guohua; Zhang, Xinyu; Jiang, Xi: Reducing simulation input-model risk via input model averaging (2021)
  3. Xu, Min; Samworth, Richard J.: High-dimensional nonparametric density estimation via symmetry and shape constraints (2021)
  4. Balabdaoui, Fadoua; Kulagina, Yulia: Completely monotone distributions: mixing, approximation and estimation of number of species (2020)
  5. Doss, Charles R.: Bracketing numbers of convex and (m)-monotone functions on polytopes (2020)
  6. Ferraccioli, Federico; Sangalli, Laura M.; Arnone, Eleonora; Finos, Livio: A functional data analysis approach to the estimation of densities over complex regions (2020)
  7. Hütter, Jan-Christian; Mao, Cheng; Rigollet, Philippe; Robeva, Elina: Optimal rates for estimation of two-dimensional totally positive distributions (2020)
  8. Jeong, Seok-Oh; Choi, Dongseok; Jang, Woncheol: A semiparametric mixture method for local false discovery rate estimation from multiple studies (2020)
  9. Lim, Eunji: The limiting behavior of isotonic and convex regression estimators when the model is misspecified (2020)
  10. Mariucci, Ester; Ray, Kolyan; Szabó, Botond: A Bayesian nonparametric approach to log-concave density estimation (2020)
  11. Royset, Johannes O.: Approximations of semicontinuous functions with applications to stochastic optimization and statistical estimation (2020)
  12. Royset, Johannes O.; Wets, Roger J-B.: Variational analysis of constrained M-estimators (2020)
  13. Chu, Lynna; Chen, Hao: Asymptotic distribution-free change-point detection for multivariate and non-Euclidean data (2019)
  14. Doss, Charles R.; Wellner, Jon A.: Univariate log-concave density estimation with symmetry or modal constraints (2019)
  15. Doss, Charles R.; Wellner, Jon A.: Inference for the mode of a log-concave density (2019)
  16. Mazumder, Rahul; Choudhury, Arkopal; Iyengar, Garud; Sen, Bodhisattva: A computational framework for multivariate convex regression and its variants (2019)
  17. Rathke, Fabian; Schnörr, Christoph: Fast multivariate log-concave density estimation (2019)
  18. Ren, Zhao; Kang, Yongjian; Fan, Yingying; Lv, Jinchi: Tuning-free heterogeneous inference in massive networks (2019)
  19. Robeva, Elina; Sturmfels, Bernd; Uhler, Caroline: Geometry of log-concave density estimation (2019)
  20. Groeneboom, Piet; Jongbloed, Geurt: Some developments in the theory of shape constrained inference (2018)

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