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 559 articles , 1 standard article )

Showing results 461 to 480 of 559.
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  1. Virili, Francesco; Freisleben, Bernd: Neural network model selection for financial time series prediction (2001)
  2. Vu, Hien T. V.; Segal, Mark R.; Knuiman, Matthew W.; James, Ian R.: Asymptotic and small sample statistical properties of random frailty variance estimates for shared gamma frailty models (2001)
  3. Yu, Keming; Moyeed, Rana A.: Bayesian quantile regression (2001)
  4. Apostolopoulos, Nikolas; Geukes, Albert; Schlittgen, Rainer: Statistics interactive! Part 1: Descriptive statistics (2000)
  5. Atkinson, Anthony; Riani, Marco: Robust diagnostic regression analysis (2000)
  6. Balkin, Sandy D.; Lin, Dennis K. J.: A neural network approach to response surface methodology (2000)
  7. Boiko, L. L.; Golubev, G. K.: How to improve the nonparametric density estimate in S-PLUS (2000)
  8. Chiu, S. N.; Quine, M. P.; Stewart, M.: Nonparametric and parametric estimation for a linear germination-growth model (2000)
  9. Dodge, Yadolah; Jurečková, Jana: Adaptive regression (2000)
  10. James Bradley; Webster West: Interactive Java Tools for Exploring High-dimensional Data (2000) not zbMATH
  11. Jean-Francois Coeurjolly: Simulation and identification of the fractional Brownian motion: a bibliographical and comparative study (2000) not zbMATH
  12. Jones, G.; Lai, C. D.; Rayner, J. C. W.: A bivariate gamma mixture distribution (2000)
  13. Krause, Andreas; Olson, Melvin: The basics of S and S-Plus. (2000)
  14. Kuhl, Michael E.; Wilson, James R.: Least squares estimation of nonhomogeneous Poisson processes (2000)
  15. Kuhnert, P. M.; Do, K.-A.; McClure, R.: Combining non-parametric models with logistic regression: an application to motor vehicle injury data. (2000)
  16. Ladd, William M.; Lindstrom, Mary J.: Self-modeling for two-dimensional response curves (2000)
  17. Lee, S. S.: Noisy replication in skewed binary classification. (2000)
  18. Lyles, Robert H.; McFarlane, Glen: Effects of covariate measurement error in the initial level and rate of change of an exposure variable (2000)
  19. Mendes, Beatriz Vaz de Melo: Assessing the bias of maximum likelihood estimates of contaminated GARCH models (2000)
  20. Pinheiro, José C.; Bates, Douglas M.: Mixed-effects models in S and S-Plus (2000)

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