Man pages for thomasWeise/regressoR.functional.models
An R Package Providing an Blueprints and Tools for Functional Models for Regression
| as.character | Convert a 'FunctionalModel' to a String |
| FunctionalModel-class | A FunctionalModel for a Functional Model |
| FunctionalModel.constant | Obtain the Simple Constant Model 'y = f(x) = a' |
| FunctionalModel.cubic | Obtain the Simple Cubic Model 'y = f(x) = a + b*x + c*x^2 +... |
| FunctionalModel.cubic.from.four.points | Compute the parameter values of a Cubic Function from four... |
| FunctionalModel.default | Obtain a List with the Default Functional Models Provided by... |
| FunctionalModel.expLogLinear.1 | Obtain the First Variant of the Exponential Log-Linear Model |
| FunctionalModel.expLogLinear.2 | Obtain the Second Variant of the Exponential Log-Linear Model |
| FunctionalModel.exponentialDecay.1 | Obtain the First Variant of the Generalized Exponential Decay... |
| FunctionalModel.exponentialDecay.2 | Obtain the Second Variant of the Generalized Exponential... |
| FunctionalModel.gompertz.1 | Obtain the First Variant of the Gompertz Model |
| FunctionalModel.gompertz.2 | Obtain the Second Variant of the Gompertz Model |
| FunctionalModel.linear | Obtain the Simple Linear Model 'y = f(x) = a+b*x' |
| FunctionalModel.linear.from.two.points | Compute the parameter values of a Linear Function from two... |
| FunctionalModel.logistic.1 | Obtain the First Variant of the Logistic Model |
| FunctionalModel.logistic.2 | Obtain the Second Variant of the Logistic Model |
| FunctionalModel.mlp | Create a Multi-Layer Perceptron Model with the Given Layers... |
| FunctionalModel.mlp.default | Get the List of Default MLP-based Models |
| FunctionalModel.mlp.monotonous | Get the List of Default Monotonously Decreasing MLP-based... |
| FunctionalModel.monotonous | Obtain a List with the Default Monotonously Decreasing... |
| FunctionalModel.new | Create a new instance of 'FunctionalModel' |
| FunctionalModel.par.check | Check that model parameters are acceptable for the functional... |
| FunctionalModel.par.estimate | Create a Parameter Estimate for a Given Functional Model |
| FunctionalModel.par.fix | Fix a Vector to be Contained in the Lower/Upper Boundaries |
| FunctionalModel.quadratic | Obtain the Simple Quadratic Model 'y = f(x) = a + b*x +... |
| FunctionalModel.quadratic.from.three.points | Compute the parameter values of a Quadratic Function from... |
