nlme

R package nlme: Linear and Nonlinear Mixed Effects Models , Fit and compare Gaussian linear and nonlinear mixed-effects models. (Source: http://cran.r-project.org/web/packages)

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 127 articles )

Showing results 1 to 20 of 127.
Sorted by year (citations)

1 2 3 ... 5 6 7 next

  1. Barrientos, Andrés F.; Peña, Víctor: Bayesian bootstraps for massive data (2020)
  2. Cong Xu, Pantelis Z. Hadjipantelis, Jane-Ling Wang: Semi-Parametric Joint Modeling of Survival and Longitudinal Data: The R Package JSM (2020) not zbMATH
  3. Emma C. Martin, Alessandro Gasparini, Michael J. Crowther: merlin: An R package for Mixed Effects Regression for Linear, Nonlinear and User-defined models (2020) arXiv
  4. Galimberti, Giuliano; Soffritti, Gabriele: Seemingly unrelated clusterwise linear regression (2020)
  5. Kappenberg, Franziska; Rahnenführer, Jörg: Book review of: C. Ritz et al., Dose response analysis using R (2020)
  6. Rainer Hirk, Kurt Hornik, Laura Vana: mvord: An R Package for Fitting Multivariate Ordinal Regression Models (2020) not zbMATH
  7. Ritz, Christian; Jensen, Signe Marie; Gerhard, Daniel; Streibig, Jens Carl: Dose-response analysis using R (2020)
  8. Tomás Capretto, Camen Piho, Ravin Kumar, Jacob Westfall, Tal Yarkoni, Osvaldo A. Martin: Bambi: A simple interface for fitting Bayesian linear models in Python (2020) arXiv
  9. Yang, Yu-Chen; Lin, Tsung-I; Castro, Luis M.; Wang, Wan-Lun: Extending finite mixtures of (t) linear mixed-effects models with concomitant covariates (2020)
  10. Addo, E. jun.; Chanda, E. K.; Metcalfe, A. V.: Spatial pair-copula model of grade for an anisotropic gold deposit (2019)
  11. Ann-Kristin Kreutzmann; Sören Pannier; Natalia Rojas-Perilla; Timo Schmid; Matthias Templ; Nikos Tzavidis: The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators (2019) not zbMATH
  12. Geraci, Marco: Modelling and estimation of nonlinear quantile regression with clustered data (2019)
  13. Graf, Monique; Marín, J. Miguel; Molina, Isabel: A generalized mixed model for skewed distributions applied to small area estimation (2019)
  14. Haziq Jamil, Wicher Bergsma: iprior: An R Package for Regression Modelling using I-priors (2019) arXiv
  15. Lee, Wonyul; Miranda, Michelle F.; Rausch, Philip; Baladandayuthapani, Veerabhadran; Fazio, Massimo; Downs, J. Crawford; Morris, Jeffrey S.: Bayesian semiparametric functional mixed models for serially correlated functional data, with application to glaucoma data (2019)
  16. Mies, Fabian; Steland, Ansgar: Nonparametric Gaussian inference for stable processes (2019)
  17. Singer, Julio M.; Rocha, Francisco M. M.; André, Carmen D. S.; Zerbini, Talita: Fitting mixed models to messy longitudinal data: a case study involving estimation of post mortem intervals (2019)
  18. Tanaka, Emi; Hui, Francis K. C.: Symbolic formulae for linear mixed models (2019)
  19. Tekbudak, Merve Yasemin; Alfaro-Córdoba, Marcela; Maity, Arnab; Staicu, Ana-Maria: A comparison of testing methods in scalar-on-function regression (2019)
  20. Wang, Wan-Lun: Mixture of multivariate (t) nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values (2019)

1 2 3 ... 5 6 7 next