New Features
- Bonferroni outlier test (#129)
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)
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.
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)
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.
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)
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.