Releases: AparicioJohan/flexFitR
Releases · AparicioJohan/flexFitR
flexFitR 1.2.0
New features
compute_tangent()function added to compute tangent line(s) for amodelerobject.inverse_predict.modeler()S3 method added to calculate inverse predictions for
modelerobjects.update.modeler()S3 method added to refit a model of classmodeler.- Adding
fn_lin_logis(),fn_quad_plat()andfn_quad_pl_sm(). predict.modeler()includesparallelandworkersto allow for parallel computing.
Changes
- When evaluating several methods in
modeler(), Jacobian and Hessian are
computed only for the best method. - Now functions are required to be vectorized (faster execution).
- Renaming
fn_lin_plat()function. - The
modeler()function now usesoptimrinstead ofopmfor faster execution. plot.modeler()includeslinewidthargument to increase size in geom lines.
Bug fixes
- Removed methods that required hessian matrix (snewton, snewtonm, snewtm) in
list_methods(). - Fixed issue when combining fitted values in
modeler().
flexFitR 1.1.0
New features
fitted.modeler()S3 method added to extract fitted values frommodelerobjects.residuals.modeler()S3 method added to extract residuals frommodelerobjects.augment()function added to calculate influence measures (Cook's distance,
leverage values, standardized residuals, studentized residuals).c.modeler()S3 method added to combinemodelerobjects.subset.modeler()S3 method added to subsetmodelerobjects.performance()function added to evaluate the performance of several models.plot.performance()S3 method to plot an object of classperformance.
Changes
modeler()adds the function name (fn_name) in every output table.modeler()no longer returns function call.plot.modeler()includesadd_ribbon_piandadd_ribbon_ciarguments for
prediction and confidence intervals.metrics()returns R2 instead of r_squared.
Bug fixes
- Fixed conflict of
modeler()with upcoming version offuture. - Fixed increase dependency to R (>=4.1).
- Fixed regression function not found in the environment when running in parallel.
v.1.0.0
- Initial CRAN submission.