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This is a patch release for urgent bug fixes.
ols_step_all_possible()
(#202)ols_step_all_possible()
(#211)ols_regress()
(#213)geom_segment()
warning in
ols_plot_obs_fit()
(#217)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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.