References in zbMATH (referenced in 20 articles )

Showing results 1 to 20 of 20.
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  1. Chakraborty, Moumita; Ghosal, Subhashis: Convergence rates for Bayesian estimation and testing in monotone regression (2021)
  2. Luo, Yao: Unobserved heterogeneity in auctions under restricted stochastic dominance (2020)
  3. Ray, Pallavi; Pati, Debdeep; Bhattacharya, Anirban: Efficient Bayesian shape-restricted function estimation with constrained Gaussian process priors (2020)
  4. Engebretsen, Solveig; Glad, Ingrid K.: Additive monotone regression in high and lower dimensions (2019)
  5. Saha, Saswati; Brannath, Werner: Comparison of different approaches for dose response analysis (2019)
  6. Seongil Jo; Taeryon Choi; Beomjo Park; Peter Lenk: bsamGP: An R Package for Bayesian Spectral Analysis Models Using Gaussian Process Priors (2019) not zbMATH
  7. Shin, Seung Jun; Ghosh, Sujit K.: A comparative study of the dose-response analysis with application to the target dose estimation (2017)
  8. Dette, Holger; Titoff, Stefanie; Volgushev, Stanislav; Bretz, Frank: Dose response signal detection under model uncertainty (2015)
  9. Karunamuni, Rohana J.; Tang, Qingguo; Zhao, Bangxin: Robust and efficient estimation of effective dose (2015)
  10. Colubi, Ana; Domínguez-Menchero, J. Santos; González-Rodríguez, Gil: Testing constancy in monotone response models (2014)
  11. Fronczyk, Kassandra; Kottas, Athanasios: A Bayesian approach to the analysis of quantal bioassay studies using nonparametric mixture models (2014)
  12. Kim, Hea-Jung; Choi, Taeryon: On Bayesian estimation of regression models subject to uncertainty about functional constraints (2014)
  13. Lin, Lizhen; Dunson, David B.: Bayesian monotone regression using Gaussian process projection (2014)
  14. Drovandi, Christopher C.; McGree, James M.; Pettitt, Anthony N.: Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data (2013)
  15. Fong, Y.; Wakefield, J.; De Rosa, S.; Frahm, N.: A robust Bayesian random effects model for nonlinear calibration problems (2012)
  16. McKay Curtis, S.; Ghosh, Sujit K.: A variable selection approach to monotonic regression with Bernstein polynomials (2011)
  17. Meyer, Mary C.; Hackstadt, Amber J.; Hoeting, Jennifer A.: Bayesian estimation and inference for generalised partial linear models using shape-restricted splines (2011)
  18. Saarela, Olli; Arjas, Elja: A method for Bayesian monotonic multiple regression (2011)
  19. Yuan, Ying; Yin, Guosheng: Dose-response curve estimation: a semiparametric mixture approach (2011)
  20. Bornkamp, Björn; Ickstadt, Katja: Bayesian nonparametric estimation of continuous monotone functions with applications to dose-response analysis (2009)