Trust |
The TrustRegionParameterCalc type exposes the following members.
Name | Description | |
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TrustRegionParameterCalc | Construct a TrustRegionParameterCalc instance using default parameters for the trust region minimization algorithm. TrustRegionMinimizer | |
TrustRegionParameterCalc(Double) | Construct a TrustRegionParameterCalc instance using the given tolerance to determine convergence of the trust region minimization algorithm. TrustRegionMinimizer | |
TrustRegionParameterCalc(Int32) | Construct a TrustRegionParameterCalc instance using the given maximum number of iterations to be performed by the trust region minimization algorithm. TrustRegionMinimizer | |
TrustRegionParameterCalc(TrustRegionMinimizer) | Construct a TrustRegionParameterCalc instance which uses the give TrustRegionMinimizer instance to calculate the parameters. TrustRegionMinimizer | |
TrustRegionParameterCalc(Int32, Double) | Construct a TrustRegionParameterCalc instance using the given maximum number of iterations to be performed by the trust region minimization algorithm, and the given tolerance used to determine convergence. TrustRegionMinimizer |
Name | Description | |
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CalculationMessage | If the algorithm succeeds the string will be empty. Otherwise it will contain information about the failure. | |
Converged | Gets a boolean indicating convergence of the trust region minimization algorithm. | |
InformationMatrix | The information matrix is the matrix of negated second partial derivations of the log likelihood function. It is the inverse of the variance/covariance matrix for the parameter estimates. | |
IsGood | Gets a boolean indicating success of failure of the calculation. | |
Iterations | Gets the number of iterations performed by the most recent calculation. | |
MaxIterations | Gets and sets the maximum number of iterations for the trust region minimization algorithm. | |
Minimizer | Gets the TrustRegionMinimizer object used to calculate the parameters. TrustRegionMinimizer |
Name | Description | |
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CalculateParameters | Calculate the parameters for the logistic model. | |
Clone | Creates a deep copy of self. |