olsrr 0.5.3.9000

New Features

• Force variables in/out in variable selection procedures
• Hierarchical selection
• Variable selection using r-squared and adjusted r-squared

Bug Fixes

• Allow users to specify threshold for detecting outliers (#178)
• If ols_test_outlier() does not find any outliers, it returns largest positive residual instead of largest absolute residual (#177)
• using 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)
• Handle extremely significant variables (#173)
• 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)
• Extracting model data (#159)
• ols_plot_resid_stud() fails to plot outliers due to y-axis range (#155)
• ols_correlations error (#191)
• Mallow’s Cp behaves inconsistently depending on model specification (#196)
• ols_step_forward_p(…) problem using the funtion ols_step_forward_p (#200)
• Output of the command “ols_step_both_aic” doesn’t contain final model (#201)

olsrr 0.5.3

CRAN release: 2020-02-10

This is a patch release to reduce the number of packages imported and fix other CRAN errors.

New Features

• Bonferroni outlier test (#129)

Breaking Changes

The following functions will now require the variable names to be enclosed within quotes

• ols_test_bartlett()
• ols_plot_resid_regressor()

olsrr 0.5.2

CRAN release: 2018-11-22

This is a minor release to fix bugs from breaking changes in recipes package and other enhancements.

Enhancements

• variable selection procedures now return the final model as an object of class lm (#81)
• data preparation functions of selected plots are now exported to enable end users to create customized plots and to use plotting library of their choice (#86)

olsrr 0.5.1

CRAN release: 2018-05-04

This is a patch release to fix minor bugs and improve error messages.

Enhancements

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.

Bug Fixes

Variable selection procedures based on p values now handle categorical variables in the same way as the procedures based on AIC values.

olsrr 0.5.0

CRAN release: 2018-03-26

This is a minor release for bug fixes and API changes.

API Changes

We have made some changes to the API to make it more user friendly:

• all the variable selection procedures start with ols_step_*
• all the test start with ols_test_*
• all the plots start with ols_plot_*

Bug Fixes

• 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)

olsrr 0.4.0

CRAN release: 2017-12-05

Enhancements

• use ols_launch_app() to launch a shiny app for building models
• save beta coefficients for each independent variable in ols_all_subset() (#41)

Bug Fixes

• mismatch in sign of partial and semi partial correlations (#44)
• error in diagnostic panel (#45)
• standardized betas in the presence of interaction terms (#46)

A big thanks goes to (Dr. Kimberly Henry) for identifying bugs and other valuable feedback that helped improve the package.

olsrr 0.3.0

CRAN release: 2017-08-31

This is a minor release containing bug fixes.

Bug Fixes

• output from reg_compute rounded up to 3 decimal points (#24)
• added variable plot fails when model includes categorical variables (#25)
• all possible regression fails when model includes categorical predictors (#26)
• output from bartlett test rounded to 3 decimal points (#27)
• best subsets regression fails when model includes categorical predictors (#28)
• output from breusch pagan test rounded to 4 decimal points (#29)
• output from collinearity diagnostics rounded to 3 decimal points (#30)
• cook’s d bar plot threshold rounded to 3 decimal points (#31)
• cook’s d chart threshold rounded to 3 decimal points (#32)
• output from f test rounded to 3 decimal points (#33)
• output from measures of influence rounded to 4 decimal points (#34)
• output from information criteria rounded to 4 decimal points (#35)
• studentized residuals vs leverage plot threshold rounded to 3 decimal points (#36)
• output from score test rounded to 3 decimal points (#37)
• step AIC backward method AIC value rounded to 3 decimal points (#38)
• step AIC backward method AIC value rounded to 3 decimal points (#39)
• step AIC both direction method AIC value rounded to 3 decimal points (#40)

olsrr 0.2.0

CRAN release: 2017-06-05

This is a minor release containing bug fixes and minor improvements.

Bug Fixes

• inline functions in model formula caused errors in stepwise regression (#2)
• added variable plots (ols_avplots) returns error when model formula contains inline functions (#3)
• all possible regression (ols_all_subset) returns an error when the model formula contains inline functions or interaction variables (#4)
• best subset regression (ols_best_subset) returns an error when the model formula contains inline functions or interaction variables (#5)
• studentized residual plot (ols_srsd_plot) returns an error when the model formula contains inline functions (#6)
• stepwise backward regression (ols_step_backward) returns an error when the model formula contains inline functions or interaction variables (#7)
• stepwise forward regression (ols_step_backward) returns an error when the model formula contains inline functions (#8)
• stepAIC backward regression (ols_stepaic_backward) returns an error when the model formula contains inline functions (#9)
• stepAIC forward regression (ols_stepaic_forward) returns an error when the model formula contains inline functions (#10)
• stepAIC regression (ols_stepaic_both) returns an error when the model formula contains inline functions (#11)
• outliers incorrectly plotted in (ols_cooksd_barplot) cook’s d bar plot (#12)
• regression (ols_regress) returns an error when the model formula contains inline functions (#21)
• output from step AIC backward regression (ols_stepaic_backward) is not properly formatted (#22)
• output from step AIC regression (ols_stepaic_both) is not properly formatted (#23)

Enhancements

• cook’s d bar plot (ols_cooksd_barplot) returns the threshold value used to classify the observations as outliers (#13)
• cook’s d chart (ols_cooksd_chart) returns the threshold value used to classify the observations as outliers (#14)
• DFFITs plot (ols_dffits_plot) returns the threshold value used to classify the observations as outliers (#15)
• deleted studentized residuals vs fitted values plot (ols_dsrvsp_plot) returns the threshold value used to classify the observations as outliers (#16)
• studentized residuals vs leverage plot (ols_rsdlev_plot) returns the threshold value used to detect outliers/high leverage observations (#17)
• standarized residuals chart (ols_srsd_chart) returns the threshold value used to classify the observations as outliers (#18)
• studentized residuals plot (ols_srsd_plot) returns the threshold value used to classify the observations as outliers (#19)

Documentation

There were errors in the description of the values returned by some functions. The documentation has been thoroughly revised and improved in this release.

olsrr 0.1.0

CRAN release: 2017-05-11

First release.