HCmodelSets: An R package for specifying sets of well-fitting models in regression with a large number of potential explanatory variables
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In the context of regression with a large number of explanatory variables, Cox and Battey (2017) emphasize that if there are alternative reasonable explanations of the data that are statistically indistinguishable, one should aim to specify as many of these explanations as is feasible. The standard practice, by contrast, is to report a single model effective for prediction. The present paper illustrates the R implementation of the new ideas in the package `HCmodelSets', using simple reproducible examples and real data. Results of some simulation experiments are also reported.
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