Man pages for OptimModel
Perform Nonlinear Regression Using 'optim' as the Optimization Engine
| beta_model | Beta hook-effect model, gradient, starting values, and... |
| exp_2o_decay | Five-parameter second-order exponential decay, gradient,... |
| exp_decay | Three-parameter exponential decay, gradient, starting values,... |
| exp_decay_pl | Three-parameter exponential decay with initial plateau,... |
| f2djac | Compute derivative with respect to parameters |
| getData | Extract data object from an optim fit |
| get_se_func | Compute standard error for a function of model parameter... |
| gompertz_model | Four-parameter Gompertz model, gradient, starting values, and... |
| hill5_model | Five-parameter Hill model, gradient, starting values, and... |
| hill_model | Four-parameter Hill model, gradient, starting values, and... |
| hill_quad_model | Five-parameter Hill model with quadratic component, gradient,... |
| hill_switchpoint_model | Five-parameter Hill model with switch point component,... |
| linear_model | Linear model, gradient, and starting values |
| nlogLik_cauchy | Negative log-likelihood function for Cauchy regression |
| optim_fit | Fit Model with optim |
| optim_weights | Weight functions for optim_fit |
| predict.optim_fit | Predicted values for optim.fit objects |
| print.optim_fit | Prints optim_fit objects |
| residuals_optim_fit | Residuals for optim.fit objects |
| rout_fitter | Fit Model with ROUT |
| rout_outlier_test | ROUT Outlier Testing |
| test_fit | Test Fit Parameters |
