This is a minor release for bug fixes and other enhancements.
p values as variable selection metricols_plot_dffits()ols_test_outlier() does not find any outliers, it returns largest positive residual instead of largest absolute residual (#177)ols_step_all_possible() with Model created from dynamic function leads to "Error in eval(model$call$data) . . . not found" (#176)ols_step_both_p(): Error in if (pvals[minp] <= pent) {: argument is of length zero (#175)ols_correlations() returns error for models with 2 predictors (#168)ols_step_both_aic() doesn’t return model (#167)ols_regress() returned residual standard error instead of RMSE (@jens-daniel-mueller, #165)This is a patch release to reduce the number of packages imported and fix other CRAN errors.
The following functions will now require the variable names to be enclosed within quotes
ols_test_bartlett()ols_plot_resid_regressor()This is a minor release to fix bugs from breaking changes in recipes package and other enhancements.
lm (#81)This is a patch release to fix minor bugs and improve error messages.
olsrr now throws better error messages keeping in mind beginner and intermediate R users. It is a work in progress and should get better in future releases.
Variable selection procedures based on p values now handle categorical variables in the same way as the procedures based on AIC values.
This is a minor release for bug fixes and API changes.
We have made some changes to the API to make it more user friendly:
ols_step_*ols_test_*ols_plot_*ols_regress returns error in the presence of interaction terms in the formula (#49)
ols_regress returns error in the presence of interaction terms in the formula (#47)
return current version (#48)
ols_launch_app() to launch a shiny app for building modelsols_all_subset() (#41)A big thanks goes to (Dr. Kimberly Henry) for identifying bugs and other valuable feedback that helped improve the package.
This is a minor release containing bug fixes.
This is a minor release containing bug fixes and minor improvements.
ols_avplots) returns error when model formula contains inline functions (#3)ols_all_subset) returns an error when the model formula contains inline functions or interaction variables (#4)ols_best_subset) returns an error when the model formula contains inline functions or interaction variables (#5)ols_srsd_plot) returns an error when the model formula contains inline functions (#6)ols_step_backward) returns an error when the model formula contains inline functions or interaction variables (#7)ols_step_backward) returns an error when the model formula contains inline functions (#8)ols_stepaic_backward) returns an error when the model formula contains inline functions (#9)ols_stepaic_forward) returns an error when the model formula contains inline functions (#10)ols_stepaic_both) returns an error when the model formula contains inline functions (#11)ols_cooksd_barplot) cook’s d bar plot (#12)ols_regress) returns an error when the model formula contains inline functions (#21)ols_stepaic_backward) is not properly formatted (#22)ols_stepaic_both) is not properly formatted (#23)ols_cooksd_barplot) returns the threshold value used to classify the observations as outliers (#13)ols_cooksd_chart) returns the threshold value used to classify the observations as outliers (#14)ols_dffits_plot) returns the threshold value used to classify the observations as outliers (#15)ols_dsrvsp_plot) returns the threshold value used to classify the observations as outliers (#16)ols_rsdlev_plot) returns the threshold value used to detect outliers/high leverage observations (#17)ols_srsd_chart) returns the threshold value used to classify the observations as outliers (#18)ols_srsd_plot) returns the threshold value used to classify the observations as outliers (#19)There were errors in the description of the values returned by some functions. The documentation has been thoroughly revised and improved in this release.
First release.