| Interface | Description |
|---|---|
| MFWithGradient |
interface for a function of several variables with a gradient
|
| MultivariateFunction |
interface for a function of several variables
|
| UnivariateFunction |
interface for a function of one variable
|
| Class | Description |
|---|---|
| Binomial |
Binomial coefficients
|
| BoundsCheckedFunction |
returns a very large number instead of the function value
if arguments are out of bound (useful for minimization with
minimizers that don't check argument boundaries)
|
| ConjugateDirectionSearch |
methods for minimization of a real-valued function of
several variables without using derivatives (Brent's modification
of a conjugate direction search method proposed by Powell)
|
| ConjugateGradientSearch |
minimization of a real-valued function of
several variables using a the nonlinear
conjugate gradient method where several variants of the direction
update are available (Fletcher-Reeves, Polak-Ribiere,
Beale-Sorenson, Hestenes-Stiefel) and bounds are respected.
|
| DifferentialEvolution |
global minimization of a real-valued function of several
variables without using derivatives using a genetic algorithm
(Differential Evolution)
|
| ErrorFunction |
error function and related stuff
|
| GammaFunction |
gamma function
|
| GeneralizedDEOptimizer |
Provides an general interface to the DifferentialEvolution class that is not
tied to a certain number of parameters (as DifferentialEvolution is).
|
| LineFunction |
converts a multivariate function into a univariate function
|
| MachineAccuracy |
determines machine accuracy
|
| MathUtils |
Handy utility functions which have some Mathematical relavance.
|
| MersenneTwisterFast |
MersenneTwisterFast:
A simulation quality fast random number generator (MT19937)
with the same public methods as java.util.Random.
|
| MultivariateMinimum |
abstract base class for minimisation of a multivariate function
|
| NumericalDerivative |
approximates numerically the first and second derivatives of a
function of a single variable and approximates gradient and
diagonal of Hessian for multivariate functions
|
| OrthogonalLineFunction |
converts a multivariate function into a univariate function
by keeping all but one argument constant
|
| OrthogonalSearch |
minimization of a real-valued function of
several variables without using derivatives, using the simple
strategy of optimizing variables one by one.
|
| StochasticOSearch |
minimization of a real-valued function of
several variables without using derivatives, using the simple
strategy of optimizing variables one by one.
|
| UnivariateMinimum |
minimization of a real-valued function of one variable
without using derivatives.
|
| UrnModel |
class for drawing numbers from an urn with and
without laying back
|
| Exception | Description |
|---|---|
| ConjugateDirectionSearch.OptimizationError |
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