Applied Regression Including Computing and Graphics

By Michael E. Hohn, Ricardo A. Olea. 1999

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Citations in the corpus

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning (2010, background): “More detailed examinations can be found in, for example, [Stein, 1999, Sasena, 2002, Diggle and Ribeiro, 2007].”
Robots that can adapt like animals (2014, background): “In (B), the reference gait is tried in all six damage conditions and its median (black line) and 25 th and 75 th percentiles (black colored area) are shown.”
Handbook of spatial statistics (2010, background): “However, we are unaware of any good statistical arguments for such a procedure and, indeed, Stein (1999) argues that an overly strong emphasis on making parametric estimates of semivariograms match the empirical semivariogram represents a serious flaw in classical geostatistics.”
Statistical Dependence: Beyond Pearson’s ρ (2018, background): “Similar considerations have been made in spatial models such as in linear Kriging models, see Stein (1999).”
Geoadditive Survival Models (2006, methodology): “The spatial component fspat(s) = βspats is assumed to follow a mean-0 stationary GRF {βspats : s ∈ R2} with variance τ 2spat and to use an isotropic covariance function cov(βspats , β spat s′ ) = C(‖s− s′‖) as proposed by Stein (1999).”
The R Commander: A Basic-Statistics Graphical User Interface to R (2005, methodology): “More ambitiously, I would like to add high-interaction statistical graphics, such as scatterplots that support dynamic variable transformations and possibly linkage between dierent plots [in the manner of Cook and Weisberg’s Lisp-Stat based Arc software ( Cook and Weisberg 1999 )].”
Joint composite estimating functions in spatiotemporal models (2012, background): “In practice, ν is difficult to estimate, because it requires dense space data and may run into identifiability problems (Stein, 1999).”