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TrustRegionParameterCalc Class

Parameter calculation for a logistic regression model. The parameters are computed to maximize the log likelihood function for the model, using a trust region optimization algorithm to compute the zeros of the first order partial derivaties of the log likelihood function. The minimization is performed by an instance of the class CenterSpace.NMath.Core.TrustRegionMinimizer and algorithms parameters may be controlled through this object. It is accessible through the Minimizer class property, and a TrustRegionParameterCalc instace may be constructed with a give TrustRegionMinimizer object which has the desired properties. TrustRegionMinimizer
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreTrustRegionParameterCalc

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
[SerializableAttribute]
public class TrustRegionParameterCalc : ILogisticRegressionCalc, 
	ICloneable

The TrustRegionParameterCalc type exposes the following members.

Constructors
  NameDescription
Public methodTrustRegionParameterCalc
Construct a TrustRegionParameterCalc instance using default parameters for the trust region minimization algorithm. TrustRegionMinimizer
Public methodTrustRegionParameterCalc(Double)
Construct a TrustRegionParameterCalc instance using the given tolerance to determine convergence of the trust region minimization algorithm. TrustRegionMinimizer
Public methodTrustRegionParameterCalc(Int32)
Construct a TrustRegionParameterCalc instance using the given maximum number of iterations to be performed by the trust region minimization algorithm. TrustRegionMinimizer
Public methodTrustRegionParameterCalc(TrustRegionMinimizer)
Construct a TrustRegionParameterCalc instance which uses the give TrustRegionMinimizer instance to calculate the parameters. TrustRegionMinimizer
Public methodTrustRegionParameterCalc(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
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Properties
  NameDescription
Public propertyCalculationMessage
If the algorithm succeeds the string will be empty. Otherwise it will contain information about the failure.
Public propertyConverged
Gets a boolean indicating convergence of the trust region minimization algorithm.
Public propertyInformationMatrix
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.
Public propertyIsGood
Gets a boolean indicating success of failure of the calculation.
Public propertyIterations
Gets the number of iterations performed by the most recent calculation.
Public propertyMaxIterations
Gets and sets the maximum number of iterations for the trust region minimization algorithm.
Public propertyMinimizer
Gets the TrustRegionMinimizer object used to calculate the parameters. TrustRegionMinimizer
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Methods
  NameDescription
Public methodCalculateParameters
Calculate the parameters for the logistic model.
Public methodClone
Creates a deep copy of self.
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See Also