Rate |
public class RateOfConversionNthOrder : IFitFunctionWithDerivative, IFitFunction, IImmutable
The RateOfConversionNthOrder type exposes the following members.
| Name | Description | |
|---|---|---|
| RateOfConversionNthOrder | Initializes a new instance of the RateOfConversionNthOrder class. |
| Name | Description | |
|---|---|---|
| NumberOfDependentVariables | Number of dependent variables (i.e. y, in Altaxo this is commonly called v (like value)). | |
| NumberOfIndependentVariables | Number of independent variables (i.e. x). | |
| NumberOfParameters | Number of parameters of this fit function. |
| Name | Description | |
|---|---|---|
| CreateFitFunction | Creates the fit function. | |
| DefaultParameterValue | Returns a default parameter value. You must ensure that the fit function would generate values with those default parameters. | |
| DefaultVarianceScaling | Returns the default variance scaling for the dependent variable i. | |
| DependentVariableName | Returns the ith dependent variable name. | |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
| Evaluate(Double, Double, Double) | This evaluates a function value. | |
| Evaluate(IROMatrixDouble, IReadOnlyListDouble, IVectorDouble, IReadOnlyListBoolean) | ||
| EvaluateConversionRate | Represents the real solution of the nth order kinetic equation y'=k*(1-y)^n with y[t0]>=0. | |
| EvaluateDerivative | This evaluates the gradient of the function with respect to the parameters. | |
| Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
| GetHashCode | Serves as the default hash function. (Inherited from Object) | |
| GetParameterBoundariesHardLimit | Gets the parameter boundaries that are really a hard limit, i.e. outside those limits, the function would probably evaluate NaN values, or makes no sense. | |
| GetParameterBoundariesSoftLimit | Gets the intended parameter boundaries. This are soft limits, boundaries so that the intended purpose of the fit function is fullfilled. Example: in the exponential decay Exp(-a*t) a is intended to be positive. This is a soft limit, and not a hard limit, because a could be also negative, and the fit nevertheless would succeed. | |
| GetType | Gets the Type of the current instance. (Inherited from Object) | |
| IndependentVariableName | Returns the ith independent variable name. | |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
| ParameterName | Returns the ith parameter name. | |
| ToString | Returns a string that represents the current object. (Inherited from Object) |