S-PLUS

S-PLUS is a powerful environment for statistical and graphical analysis of data. It provides the tools to implement many standard and modern statistical methods made possible by the widespread availability of workstations having good graphics and computational capabilities.


References in zbMATH (referenced in 600 articles , 1 standard article )

Showing results 1 to 20 of 600.
Sorted by year (citations)

1 2 3 ... 28 29 30 next

  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. Diabaté, Modibo; Coquille, Loren; Samson, Adeline: Parameter estimation and treatment optimization in a stochastic model for immunotherapy of cancer (2020)
  4. Everitt, Brian S.: A handbook of statistical analyses using S-PLUS (2020)
  5. Fuino, Michel; Wagner, Joël: Duration of long-term care: socio-economic factors, type of care interactions and evolution (2020)
  6. Galarza, Christian E.; Castro, Luis M.; Louzada, Francisco; Lachos, Victor H.: Quantile regression for nonlinear mixed effects models: a likelihood based perspective (2020)
  7. Hall, P.; Johnstone, I. M.; Ormerod, J. T.; Wand, M. P.; Yu, J. C. F.: Fast and accurate binary response mixed model analysis via expectation propagation (2020)
  8. Javeed, Aurya; Hooker, Giles: Timing observations of diffusions (2020)
  9. Nolan, Tui H.; Wand, Matt P.: Streamlined solutions to multilevel sparse matrix problems (2020)
  10. 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)
  11. Reynolds, Angus; Kvam, Peter D.; Osth, Adam F.; Heathcote, Andrew: Correlated racing evidence accumulator models (2020)
  12. Roustant, Olivier; Padonou, Espéran; Deville, Yves; Clément, Aloïs; Perrin, Guillaume; Giorla, Jean; Wynn, Henry: Group kernels for Gaussian process metamodels with categorical inputs (2020)
  13. Shao, Yuanyuan; McKean, Joseph W.; Huitema, Bradley E.: Traditional and rank-based tests for ordered alternatives in a cluster correlated model (2020)
  14. Xu, Ancha; Wang, You-Gan; Zheng, Shurong; Cai, Fengjing: Bias reduction in the two-stage method for degradation data analysis (2020)
  15. Baey, Charlotte; Cournède, Paul-Henry; Kuhn, Estelle: Asymptotic distribution of likelihood ratio test statistics for variance components in nonlinear mixed effects models (2019)
  16. Carpita, Maurizio; Ciavolino, Enrico; Pasca, Paola: Exploring and modelling team performances of the kaggle European soccer database (2019)
  17. Conde-Amboage, Mercedes; Sánchez-Sellero, César: A plug-in bandwidth selector for nonparametric quantile regression (2019)
  18. 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)
  19. Flores-Agreda, Daniel; Cantoni, Eva: Bootstrap estimation of uncertainty in prediction for generalized linear mixed models (2019)
  20. 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)

1 2 3 ... 28 29 30 next