title: “manymodelr-News” author: “Nelson Gonzabato” output: htlm_document

manymodelr 0.2.3

New functions

  1. plot_corr has been added to allow plotting of correlation matrices produced by get_var_corr_.

  2. na_replace_grouped extends na_replace by allowing replacement of missing values(NAs) by group.

  3. add_model_predictions allows addition of predicted values to a data set.

  4. add_model_residuals is an easy to use and dplyr compatible wrapper that allows addition of residuals to a data set.

  5. extract_model_info allows easy extraction of common model attributes such as p values, residuals, coefficients, etc as per the specific model type. It supports extraction of multiple attributes.

  6. multi_model_2 allows fitting and predicting in one function. It is similar to multi_model_1 except it does not require metrics.

Major Changes

  1. modeleR has been replaced with fit_model which is an easier to remember name. Usage remains the same.

  2. fit_model no longer allows direct addition of predictions. Use add_model_predictions to achieve the same.

  3. na_replace has been extended to allow for user defined values.

  4. rowdiff now accepts replacement of the calculation induced NAs. It does so by using na_replace.

  5. get_var_corr_ now supports using only a subset of the data.

  6. Helper functions are no longer exported.

  7. get_data_Stats is now aliased with get_stats for ease.

  8. get_var_corr no longer has the get_all argument. Instead, users can provide an option other_vars vector of subset columns. drop_columns has also been changed from boolean to a character vector.


manymodelr 0.2.2

Minor bug fixes with respect to the vignette.


manymodelr 0.2.1

Major Changes

Additions

  1. agg_by_group is a new function that manipulates grouped data. It is fast and robust for many kinds of functions.

  2. rowdiff is another new function that enable one to find differences between rows in a data.frame object. `

  3. get_var_corr provides a user-friendly way to find correlations between data.

  4. get_var_corr_ provides a user-friendly way to find combination-wise correlations. It is relatively fast depending on how big one’s data is and/or machine specifications.

  5. get_this is an easy to use helper function to get metrics,predictions, etc. Currently supports lists and data.frame objects.

  6. modeleR and row_mean_na were removed.

Major Modifications

  1. get_data_Stats now supports removal of missing data as well as using only numeric data.

  2. modeleR has been fixed to handle new data as expected. It also now supports glm.

  3. multi_model_1 now supports either validation or working with new data.

  4. row_mean_na has been replaced with na_replace which is more robust. row_mean_na will be removed in future versions.