- Small fix to docs.
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New cv.function() method meant to replace cvSelect(), direct use of which is now discouraged.
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New selectModelList() to be used with cv.function() (or with cvSelect()). selectModelList() implements recursive cross-validation, where the fit of a model selected by CV is assessed by CV. The same procedure is also available by setting recursive=TRUE in a call to cv.modList().
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cv.default() and other cv() methods acquire a details argument, which if TRUE includes information about the folds in the returned object.
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New as.data.frame.cv() and related methods for turning the detailed results returned by cv() methods into a data frame, with new print() and summary() methods for the objects produced.
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Improvements to code, introducing folds(), fold(), and related functions.
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Refactoring of code; cv() methods now all call cvCompute() (which is new), cvMixed(), or cvSelect().
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Reorganization of package file structure and of documentation.
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Make the cv.default() method more robust, particularly for parallel computations.
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Reorganize package vignettes (of which there are now 5).
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Other small improvements.
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cv() et al. now work properly with "non-casewise average" CV criteria such as the new rmse() and medAbsErr(), not just with "casewise-average" fit criteria such as mse() and BayesRule().
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Bias adjustment and confidence intervals (which are new) are computed only for casewise-average CV criteria. Demonstrate that 1 - AUC isn't a casewise-average criterion.
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Generally suppress spurious messages about setting the seed in cv.modList() for LOO CV.
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Fix bugs in selectTrans() that caused errors when one of response and predictors arguments not specified.
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Fix bug in cvMixed() that prevented parallel computations (reported by Craig See).
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Fix small bug in cvSelect(), returning properly named "coefficients" element when save.coef is TRUE.
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Fix bug in cv.lm() and cv.glm() with method="hatvalues" for cost criteria other than mse().
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Add selectTransStepAIC() procedure for use with cvSelect().
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Add medAbsErr() and rmse() cost criteria.
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Add coef.cvSelect() method.
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Add cv.rlm() method.
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plot.cvModList() can show averages +/- SDs, and averages and CIs, as well as averages and ranges.
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Add Pigs data set.
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change getResponse() and methods to GetResponse() to avoid name clash with nlme.
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Improvements and updates to documentation, and expanded cv.Rmd vignette.
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Mixed-models methods no longer flagged as "experimental."
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Mixed-models CV functions no longer limited to nested random effects.
- Initial CRAN version.
- Initial version.