Uses of Package
net.finmath.optimizer
Package
Description
Classes related to the calibration of Fourier models.
Provides some static functions, e.g., analytic valuation formulas or functions from linear algebra.
Provides classes to create a calibrated model of curves from a collection of calibration
products and corresponding target values.
Provides interface specification and implementation of volatility surfaces, e.g.,
interest rate volatility surfaces like (implied) caplet volatilities and swaption
volatilities.
Provides classes to create a calibrated model of curves from a collection of calibration
products and corresponding target values.
This package provides classes with numerical algorithm for optimization of
an objective function and a factory to easy construction of the optimizers.
Classes providing calibration to market data of volatility cubes.
Provides interface specification and implementation of volatility cubes, as well as a factory to create these, either via calibration from market data or construction
from parameters.
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ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionThis class implements a Golden Section search algorithm, i.e., a minimization, implemented as a question-and-answer search algorithm.This class implements a parallel Levenberg-Marquardt non-linear least-squares fit algorithm.The regularization method used to invert the approximation of the Hessian matrix.Interface for numerical optimizers.Interface for the objective function.Exception thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
.This class implements a stochastic Levenberg Marquardt non-linear least-squares fit algorithm.The regularization method used to invert the approximation of the Hessian matrix.The interface describing the objective function of aStochasticOptimizer
.This class implements a stochastic Levenberg Marquardt non-linear least-squares fit algorithm. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
. -
ClassDescriptionException thrown by solvers
invalid @link
net.finmath.rootfinder
net.finmath.optimizer
.