Applied Regression Analysis

By N. Draper, H. Smith. 1966

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Extended Comparisons of Best Subset Selection, Forward Stepwise Selection, and the Lasso (2017, neutral): “…are classical methods in statistics, dating back to at least Beale et al. (1967); Hocking and Leslie (1967) for best subset selection and Efroymson (1966); Draper and Smith (1966) for forward selection; the lasso is (relatively speaking) more recent, due to Tibshirani (1996); Chen et al. (1998).”
Locally Weighted Learning (1997, methodology): “Techniques for selecting features in the distance metric and local model have been developed in statistics (Draper and Smith, 1981; Miller, 1990), including all subsets, forward regression, backwards regression, and stepwise regression.”
A comparison of classification techniques for the P300 Speller (2006, methodology): “Determining the presence or absence of a P300 evoked potential from EEG features can be considered a binary classification problem with a discriminant function having a decision hyper-plane defined by: 0 where x is the feature vector, f( ⋅ ) is a transformation function, w is a vector of…”
Environmental influences on larval duration, growth and magnitude of settlement of a coral reef fish (2005, background): “Mallow’s Cp measures the best possible fit of a model based on whether or not the error mean square contains only random variation (Draper and Smith 1981).”