References in zbMATH (referenced in 170 articles , 1 standard article )

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  1. Argiento, Raffaele; Cremaschi, Andrea; Vannucci, Marina: Hierarchical normalized completely random measures to cluster grouped data (2020)
  2. Cunen, Céline; Walløe, Lars; Hjort, Nils Lid: Focused model selection for linear mixed models with an application to whale ecology (2020)
  3. Galarza, Christian E.; Castro, Luis M.; Louzada, Francisco; Lachos, Victor H.: Quantile regression for nonlinear mixed effects models: a likelihood based perspective (2020)
  4. Javeed, Aurya; Hooker, Giles: Timing observations of diffusions (2020)
  5. Pullenayegum, Eleanor M.: Meeting the assumptions of inverse-intensity weighting for longitudinal data subject to irregular follow-up: suggestions for the design and analysis of clinic-based cohort studies (2020)
  6. Roustant, Olivier; Padonou, Espéran; Deville, Yves; Clément, Aloïs; Perrin, Guillaume; Giorla, Jean; Wynn, Henry: Group kernels for Gaussian process metamodels with categorical inputs (2020)
  7. Xu, Ancha; Wang, You-Gan; Zheng, Shurong; Cai, Fengjing: Bias reduction in the two-stage method for degradation data analysis (2020)
  8. Baey, Charlotte; Cournède, Paul-Henry; Kuhn, Estelle: Asymptotic distribution of likelihood ratio test statistics for variance components in nonlinear mixed effects models (2019)
  9. Das, Sumonkanti; Rahman, Azizur; Ahamed, Ashraf; Rahman, Sabbir Tahmidur: Multi-level models can benefit from minimizing higher-order variations: an illustration using child malnutrition data (2019)
  10. Flores-Agreda, Daniel; Cantoni, Eva: Bootstrap estimation of uncertainty in prediction for generalized linear mixed models (2019)
  11. Fu, Liyong; Wang, Mingliang; Wang, Zuoheng; Song, Xinyu; Tang, Shouzheng: Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming (2019)
  12. García, Oscar: Estimating reducible stochastic differential equations by conversion to a least-squares problem (2019)
  13. Geraci, Marco: Modelling and estimation of nonlinear quantile regression with clustered data (2019)
  14. Heck, Daniel W.: Accounting for estimation uncertainty and shrinkage in Bayesian within-subject intervals: a comment on Nathoo, Kilshaw, and Masson (2018) (2019)
  15. Pelamatti, Julien; Brevault, Loïc; Balesdent, Mathieu; Talbi, El-Ghazali; Guerin, Yannick: Efficient global optimization of constrained mixed variable problems (2019)
  16. Plasse, Joshua; Adams, Niall M.: Multiple changepoint detection in categorical data streams (2019)
  17. Scealy, J. L.; Wood, Andrew T. A.: Scaled von Mises-Fisher distributions and regression models for paleomagnetic directional data (2019)
  18. Audigier, Vincent; White, Ian R.; Jolani, Shahab; Debray, Thomas P. A.; Quartagno, Matteo; Carpenter, James; van Buuren, Stef; Resche-Rigon, Matthieu: Multiple imputation for multilevel data with continuous and binary variables (2018)
  19. Bowman, Adrian W.: Big questions, informative data, excellent science (2018)
  20. Cederbaum, Jona; Scheipl, Fabian; Greven, Sonja: Fast symmetric additive covariance smoothing (2018)

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