nlme

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)

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References in zbMATH (referenced in 34 articles )

Showing results 1 to 20 of 34.
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  1. Agasisti, Tommaso; Ieva, Francesca; Paganoni, Anna Maria: Heterogeneity, school-effects and the north/south achievement gap in Italian secondary education: evidence from a three-level mixed model (2017)
  2. Kühnel, Line; Sommer, Stefan; Pai, Akshay; Raket, Lars Lau: Most likely separation of intensity and warping effects in image registration (2017)
  3. Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant: Boosted multivariate trees for longitudinal data (2017)
  4. Paul-Christian Buerkner: Bayesian Distributional Non-Linear Multilevel Modeling with the R Package brms (2017) arXiv
  5. Kogan, Clark; Kalachev, Leonid; Van Dongen, Hans P.A.: Prediction accuracy in multivariate repeated-measures Bayesian forecasting models with examples drawn from research on sleep and circadian rhythms (2016)
  6. Zorick, Todd; Smith, Jason: Generalized information equilibrium approaches to EEG sleep stage discrimination (2016)
  7. Bertsimas, Dimitris; Brynjolfsson, Erik; Reichman, Shachar; Silberholz, John: OR forum: Tenure analytics: models for predicting research impact (2015)
  8. Charnigo, Richard; Feng, Limin; Srinivasan, Cidambi: Nonparametric and semiparametric compound estimation in multiple covariates (2015)
  9. McLean, Mathew W.; Hooker, Giles; Ruppert, David: Restricted likelihood ratio tests for linearity in scalar-on-function regression (2015)
  10. Choudhary, Pankaj K.; Sengupta, Dishari; Cassey, Phillip: A general skew-$t$ mixed model that allows different degrees of freedom for random effects and error distributions (2014)
  11. Delattre, Maud; Lavielle, Marc; Poursat, Marie-Anne: A note on BIC in mixed-effects models (2014)
  12. Dimitris Rizopoulos: The R Package JMbayes for Fitting Joint Models for Longitudinal and Time-to-Event Data using MCMC (2014) arXiv
  13. Finch, W. Holmes; Bolin, Jocelyn E.; Kelley, Ken: Multilevel modeling using R (2014)
  14. Hofner, Benjamin; Mayr, Andreas; Robinzonov, Nikolay; Schmid, Matthias: Model-based boosting in R: a hands-on tutorial using the R package mboost (2014)
  15. Swenson, Nathan G.: Functional and phylogenetic ecology in R (2014)
  16. Bollandsås, Ole Martin; Gregoire, Timothy G.; Næsset, Erik; Øyen, Bernt-Håvard: Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data (2013)
  17. Gałecki, Andrzej; Burzykowski, Tomasz: Linear mixed-effects models using R. A step-by-step approach (2013)
  18. Jones, Geoff: Book review of: D. Rizopoulos, Joint models for longitudinal and time-to-event data. With applications in R (2013)
  19. Montoya, Eduardo L.; Meiring, Wendy: On the relative efficiency of a monotone parameter curve estimator in a functional nonlinear model (2013)
  20. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2013)

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