Statistical Models in S

By J. Chambers, Trevor J. Hastie. 1991

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Citations in the corpus

Visualizing the effects of predictor variables in black box supervised learning models (2016, background): “Conditioning plots (coplots) (Chambers and Hastie (1992); Cleveland (1993)), conditional response (CORE) plots (Cook (1995)), and individual conditional expectation (ICE) plots (Goldstein and Pitkin (2015)) plot quantities like f(xj ,x\j) vs.”
Edward: A library for probabilistic modeling, inference, and criticism (2016, background): “The S language, developed by John Chambers and colleagues at Bell Laboratories (Becker and Chambers, 1984; Chambers and Hastie, 1992), focused on an interactive environment for data analysis, with simple yet rich syntax to quickly turn ideas into software.”
The VGAM Package for Categorical Data Analysis (2010, background): “Another alternative is to add extra terms such as interaction terms into the linear predictor (available in the S language; Chambers and Hastie 1993).”
Satellite Based Mapping of Ground PM2.5 Concentration Using Generalized Additive Modeling (2016, methodology): “This step algorithm uses the Akaike information criterion (AIC) statistic, taking into account both the information explained by the model and its complexity to evaluate models [41].”
Generalized Additive Models for Location Scale and Shape (GAMLSS) in R (2007, methodology): “For modelling linear functions the Wilkinson and Rogers (1973) notation as applied for model formulae in the S language by Chambers and Hastie (1992) can be used.”
Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models (2004, methodology): “, the Chambers and Hastie 1993, discussion of smooth.spline) and σ 2 is the variance of the yi or, in a P–IRLS context, the scale parameter. Neither criteria is easy to minimize with respect to multiple smoothing parameters, because direct evaluation of the tr(A) term involves at least nq2/2 operati”
The R Commander: A Basic-Statistics Graphical User Interface to R (2005, methodology): “For more information on specifying models, see the Introduction to R manual that comes with R, which may be accessed from the Help menu in the R Console, or a general treatment of statistical modeling in S, such as Chambers and Hastie (1992), Fox (2002), or Venables and Ripley (2002).”
An investigation into parametric models for mortality projections, with applications to immediate annuitants' and life office pensioners' data (2000, methodology): “For this study, implementation was carried out using S-PLUS and details of statistical modelling in S-PLUS can be found in Chambers and Hastie (1993) and Venables and Ripley (1994).”