Flexible Non-Linear Least Square Model Fitting
Extra Sum-of-Squares F-Test for modeler objects
Augment a modeler object with influence diagnostics
Combine objects of class modeler
Coefficients for an object of class modeler
Compute tangent line(s) from a modeler object
Confidence intervals for a modeler object
Delta method AUC estimation
Delta method for derivative estimation
Delta method generic function
Delta method point estimation
General-purpose optimization
Explore data
Function for AUC estimation
Function for derivatives
Function for point estimation
Extract fitted values from a modeler object
flexFitR: Flexible Non-Linear Least Square Model Fitting
Double-exponential function
Exponential-linear function
Super-exponential exponential function
Super-exponential linear function
Linear-logistic function
Linear plateau linear function
Linear plateau linear with constrains
Linear plateau function
Linear function
Logistic function
Smooth Quadratic-plateau function
Quadratic-plateau function
Quadratic function
Akaike's An Information Criterion for an object of class modeler
Inverse prediction from a modeler object
Generic for inverse prediction
Print available functions in flexFitR
Print available methods in flexFitR
Extract Log-Likelihood for an object of class modeler
Metrics for an object of class modeler
Modeler: Non-linear regression for curve fitting
Compare performance of different models
Plot user-defined function
Plot an object of class explorer
Plot an object of class modeler
Plot an object of class performance
Predict an object of class modeler
Print an object of class modeler
Extract residuals from a modeler object
Transform variables in a data frame
Subset an object of class modeler
Update a modeler object
Variance-Covariance matrix for an object of class modeler
Provides tools for flexible non-linear least squares model fitting using general-purpose optimization techniques. The package supports a variety of optimization algorithms, including those provided by the 'optimx' package, making it suitable for handling complex non-linear models. Features include parallel processing support via the 'future' and 'foreach' packages, comprehensive model diagnostics, and visualization capabilities. Implements methods described in Nash and Varadhan (2011, <doi:10.18637/jss.v043.i09>).
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