![]() | NewtonRaphsonParameterCalc Class |
Namespace: CenterSpace.NMath.Core
The NewtonRaphsonParameterCalc type exposes the following members.
Name | Description | |
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![]() | NewtonRaphsonParameterCalc |
Constructs a NewtonRaphsonParameterCalc object with a default
tolerance of 1e-8, and a default value of 1000 for the maximum number of
iterations.
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![]() | NewtonRaphsonParameterCalc(Double) |
Constructs a NewtonRaphsonParameterCalc object with the given
tolerance. A default value of 1000 is used for the maximum number of
iterations.
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![]() | NewtonRaphsonParameterCalc(Int32) |
Constructs a NewtonRaphsonParameterCalc object with the given
maximum number of iterations. A default value of 1e-8 is used for the
tolerance.
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![]() | NewtonRaphsonParameterCalc(Int32, Double) |
Constructs a NewtonRaphsonParameterCalc object with the given
maximum number of iterations and tolerance.
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![]() | NewtonRaphsonParameterCalc(Int32, Double, Boolean) |
Constructs a NewtonRaphsonParameterCalc object with the given
maximum number of iterations and tolerance.
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Name | Description | |
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![]() | CalculationMessage |
This string will contain information about algorithm failure, or
if the regression matrix is rank deficient and pseudo inverses
were used. Otherwise it will be empty.
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![]() | Converged |
Gets a boolean value indicating whether or not the algorithm
converged.
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![]() | FailIfNotFullRank |
Gets and sets a boolean value indicating whether or not parameter
calculation should fail if the input matrix of observed values, the
regression matrix does not have full rank. The default value is
false.
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![]() | 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.
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![]() | IsGood |
Gets a boolean indicating success of failure of the calculation.
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![]() | Iterations |
Gets the number of iterations performed by the algorithm.
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![]() | MaxIterations |
Gets the sets the maximum number of iterations performed by the algorithm.
Default is 1000.
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![]() | SolutionChange |
Gets the change in the solution value on the last iteration of the
algorithm.
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![]() | Tolerance |
Gets and sets the tolerance used to determine convergence of the algorithm.
The algorithm is judged converged when the norm of the solution change is
less than Tolerance * max(B), where max(B) is the magnitude
of the largest solution component.
Default value is 1e-8.
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Name | Description | |
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![]() | CalculateParameters |
Calculate the parameters for the logistic model.
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![]() | Clone |
Creates a deep copy of self.
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