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 615 articles , 1 standard article )

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  1. Abbaszadeh, D.; Tavassoli Kajani, M.; Momeni, M.; Zahraei, M.; Maleki, M.: Solving fractional Fredholm integro-differential equations using Legendre wavelets (2021)
  2. Casa, Alessandro; Bouveyron, Charles; Erosheva, Elena; Menardi, Giovanna: Co-clustering of time-dependent data via the shape invariant model (2021)
  3. Castellano, Rosella; Mancinelli, Marco; Ponsi, Giorgia; Tieri, Gaetano: What if versus probabilistic scenarios: a neuroscientific analysis (2021)
  4. Delattre, Maud: A review on asymptotic inference in stochastic differential equations with mixed effects (2021)
  5. Hančová, Martina; Gajdoš, Andrej; Hanč, Jozef; Vozáriková, Gabriela: Estimating variances in time series kriging using convex optimization and empirical BLUPs (2021)
  6. Hoff, Peter: Additive and multiplicative effects network models (2021)
  7. Larbi, Yassine Ou; El Halimi, Rachid; Akharif, Abdelhadi; Mellouk, Amal: Optimal tests for random effects in linear mixed models (2021)
  8. Mauff, Katya; Erler, Nicole S.; Kardys, Isabella; Rizopoulos, Dimitris: Pairwise estimation of multivariate longitudinal outcomes in a Bayesian setting with extensions to the joint model (2021)
  9. M. Helena Gonçalves, M. Salomé Cabral: cold: An R Package for the Analysis of Count Longitudinal Data (2021) not zbMATH
  10. Mota, Alex; Milani, Eder A.; Calsavara, Vinicius F.; Tomazella, Vera L. D.; Leão, Jeremias; Ramos, Pedro L.; Ferreira, Paulo H.; Louzada, Francisco: Weighted Lindley frailty model: estimation and application to lung cancer data (2021)
  11. Schumacher, Fernanda L.; Dey, Dipak K.; Lachos, Victor H.: Approximate inferences for nonlinear mixed effects models with scale mixtures of skew-normal distributions (2021)
  12. Wang, Meng; Jiang, Lihua; Snyder, Michael P.: AdaReg: data adaptive robust estimation in linear regression with application in GTEx gene expressions (2021)
  13. Akdur, Hatice Tul Kubra; Ozonur, Deniz; Bayrak, Hulya: An adaptation of pseudo-score confidence interval method for linear mixed models (2020)
  14. Argiento, Raffaele; Cremaschi, Andrea; Vannucci, Marina: Hierarchical normalized completely random measures to cluster grouped data (2020)
  15. Burgaard, Johan; Steffensen, Mogens: Eliciting risk preferences and elasticity of substitution (2020)
  16. Cunen, Céline; Walløe, Lars; Hjort, Nils Lid: Focused model selection for linear mixed models with an application to whale ecology (2020)
  17. Diabaté, Modibo; Coquille, Loren; Samson, Adeline: Parameter estimation and treatment optimization in a stochastic model for immunotherapy of cancer (2020)
  18. Everitt, Brian S.: A handbook of statistical analyses using S-PLUS (2020)
  19. Fuino, Michel; Wagner, Joël: Duration of long-term care: socio-economic factors, type of care interactions and evolution (2020)
  20. Galarza, Christian E.; Castro, Luis M.; Louzada, Francisco; Lachos, Victor H.: Quantile regression for nonlinear mixed effects models: a likelihood based perspective (2020)

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