Skip to contents

flexFitR 1.1.0.00009

New features

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 uses optimr instead of opm for faster execution.
  • plot.modeler() includes linewidth argument 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

CRAN release: 2025-02-21

New features

  • fitted.modeler() S3 method added to extract fitted values from modeler objects.
  • residuals.modeler() S3 method added to extract residuals from modeler objects.
  • augment() function added to calculate influence measures (Cook’s distance, leverage values, standardized residuals, studentized residuals).
  • c.modeler() S3 method added to combine modeler objects.
  • subset.modeler() S3 method added to subset modeler objects.
  • performance() function added to evaluate the performance of several models.
  • plot.performance() S3 method to plot an object of class performance.

Changes

  • modeler() adds the function name (fn_name) in every output table.
  • modeler() no longer returns function call.
  • plot.modeler() includes add_ribbon_pi and add_ribbon_ci arguments for prediction and confidence intervals.
  • metrics() returns R2 instead of r_squared.

Bug fixes

  • Fixed conflict of modeler() with upcoming version of future.
  • Fixed increase dependency to R (>=4.1).
  • Fixed regression function not found in the environment when running in parallel.

flexFitR 1.0.0

CRAN release: 2025-01-20

flexFitR 0.1.0

  • Initial CRAN submission.