Uses of Interface
function.VariableInputDimension

Packages that use VariableInputDimension

data	Provides classes for handling sets of double-valued input-output data.
diviner	Provides functionality for measuring the level of promise of a design candidates.
function	Provides classes for scalar and vector-valued functions that operate on multi- dimensional double-valued data.
model	Provides classes that handle various kinds of approximation models, data fits, and so on.

Uses of VariableInputDimension in data

Classes in data that implement VariableInputDimension

class

DataPoint Class to store an input-output pair, called a DataPoint.

Uses of VariableInputDimension in diviner

Subinterfaces of VariableInputDimension in diviner

interface

MultiObjectiveDiviner A diviner that uses multiple objectives as measures of promise.

Classes in diviner that implement VariableInputDimension

class	BasicBoundConstrainedDiviner Implements basic functionality for BoundConstrainedDiviner.
class	BasicInequalityConstrainedDiviner Basic diviner for inequality-constrained problems.
class	BasicMultiObjectiveDiviner
class	ConstrainedEIDiviner Constrained version of the EIDiviner.
class	ConstrainedImprovementDiviner ImprovementDiviner for constrained problems.
class	ConstrainedMultiMetricDiviner Multi-metric diviner for constrained problems.
class	EIDiviner Implements an expected improvement BoundConstrainedDiviner.
class	ImprovementDiviner Focuses on various ways of divining merit using the posterior distribution at a point and some computation of improvement.
class	MultiMetricDiviner Uses multiple figures of merit to compute 'goodness' of a point for sampling.
class	PIDiviner Implements a diviner based on probability of improvement.
class	RiskDiviner Another way of trading performance and risk: quantify the risk as the probability of not achieving a given performance.
class	RiskPerfTradeDiviner BoundConstrainedDiviner that returns mean - k*stdDev.
class	RiskPerfTypeIDiviner Multiobjective diviner that uses mu and sigma as objectives to be simultaneously minimized.
class	RiskPerfTypeIIDiviner Multiobjective diviner that uses mu - k*sigma and sigma as objectives to be simultaneously minimized.
class	RiskPerfTypeIIIDiviner Multiobjective diviner that uses mu - k*sigma and mu as objectives to be simultaneously minimized.
class	RiskPerfTypeIVDiviner Multiobjective diviner that uses mu and -sigma as objectives to be simultaneously minimized.
class	RiskPerfTypeVDiviner Multiobjective diviner that uses mu - k*sigma and mu + k*sigma as objectives to be simultaneously minimized.

Uses of VariableInputDimension in function

Classes in function that implement VariableInputDimension

class	Rosenbrock Extended Rosenbrock function, defined for an even number of input dimensions.
class	RosenbrockLoFi Implements the Rosenbrock function minus one quadratic term.
class	VariableDomainScalarFunction Abstract class for scalar functions with variable input dimensionality.
class	VectorFunctionBuilder Compose a vector function out of individual ScalarFunctions and VectorFunctions.

Uses of VariableInputDimension in model

Subinterfaces of VariableInputDimension in model

interface	ApproxModel Extends the DataFit interface by supporting methods that compute the uncertainty at a point in addition to a value.
interface	DataFit A DataFit is a ScalarFunction that also provides the VariableInputDimension and VariableBounds interfaces, thereby allowing its DEFAULT_BOUNDS and dimensionality to be modified.
interface	TwoFidelityApproxModel Fits an approximate model to the difference between given data and a low-order approximation of the oracle that generated that data.

Classes in model that implement VariableInputDimension

class	BasicApproxModel Basic implementation of the methods in ApproxModel.
class	BasicCorrelationFunction Basic implementation of a correlation function for GPs.
class	BasicTwoFidelityModel Basic two-fidelity approximation model, using an additive surrogate correction.
class	DifferentiableCorrelationFunction A correlation function which is differentiable w.r.t its length-scale parameters.
class	ExponentialCorrelationFunction Exponential correlation function.
class	GPRegression Creation process: Set tau (compulsory), set prior mean and covariance, set bounds, init().
class	PenaltyFunctionModel Computes mean and variance for an external penalty function augmented Lagrangian.
class	SECorrelationFunction Squared exponential correlation function.