ROL::MeanVarianceFromTarget< Real > Class Template Reference

Provides an interface for the mean plus a sum of arbitrary order variances from targets. More...

#include <ROL_MeanVarianceFromTarget.hpp>

Inheritance diagram for ROL::MeanVarianceFromTarget< Real >:

Public Member Functions
	MeanVarianceFromTarget (const Real target, const Real order, const Real coeff, const ROL::Ptr< PositiveFunction< Real > > &pf)
	Constructor.
	MeanVarianceFromTarget (const std::vector< Real > &target, const std::vector< Real > &order, const std::vector< Real > &coeff, const ROL::Ptr< PositiveFunction< Real > > &pf)
	Constructor.
	MeanVarianceFromTarget (ROL::ParameterList &parlist)
	Constructor.
void	updateValue (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
void	updateGradient (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)
void	updateHessVec (Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol)

Private Types
typedef std::vector< Real >::size_type	uint

Private Member Functions
void	checkInputs (void) const

Private Attributes
ROL::Ptr< PositiveFunction< Real > >	positiveFunction_
std::vector< Real >	target_
std::vector< Real >	order_
std::vector< Real >	coeff_
uint	NumMoments_

Detailed Description

template<class Real>
class ROL::MeanVarianceFromTarget< Real >

Provides an interface for the mean plus a sum of arbitrary order variances from targets.

The mean plus variances from targets risk measure is

\[ \mathcal{R}(X) = \mathbb{E}[X] + \sum_{k=1}^n c_k \mathbb{E}[\wp(X-t_k)^{p_k}] \]

where \(\wp:\mathbb{R}\to[0,\infty)\) is either the absolute value or \((x)_+ = \max\{0,x\}\), \(c_k > 0\) and \(p_k\in\mathbb{N}\). \(\mathcal{R}\) is law-invariant, but not coherent since it violates positive homogeneity and translation equivariance.

When using derivative-based optimization, the user can provide a smooth approximation of \((\cdot)_+\) using the ROL::PositiveFunction class.

Definition at line 43 of file ROL_MeanVarianceFromTarget.hpp.

Member Typedef Documentation

uint

template<class Real>

typedef std::vector<Real>::size_type ROL::MeanVarianceFromTarget< Real >::uint

private

Definition at line 44 of file ROL_MeanVarianceFromTarget.hpp.

Constructor & Destructor Documentation

MeanVarianceFromTarget() [1/3]

template<class Real>

ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget ( const Real target, const Real order, const Real coeff, const ROL::Ptr< PositiveFunction< Real > > & pf )

inline

Constructor.

Parameters

[in]	target	is the scalar target
[in]	order	is the variance order
[in]	coeff	is the weight for variance term
[in]	pf	is the plus function or an approximation

This constructor produces a mean plus variance from target risk measure with a single variance.

Definition at line 92 of file ROL_MeanVarianceFromTarget.hpp.

References checkInputs(), coeff_, NumMoments_, order_, positiveFunction_, and target_.

MeanVarianceFromTarget() [2/3]

template<class Real>

ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget ( const std::vector< Real > & target, const std::vector< Real > & order, const std::vector< Real > & coeff, const ROL::Ptr< PositiveFunction< Real > > & pf )

inline

Constructor.

Parameters

[in]	target	is a vector of targets
[in]	order	is a vector of variance orders
[in]	coeff	is a vector of weights for the variance terms
[in]	pf	is the plus function or an approximation

This constructor produces a mean plus variance from target risk measure with an arbitrary number of variances.

Definition at line 112 of file ROL_MeanVarianceFromTarget.hpp.

References checkInputs(), coeff_, NumMoments_, order_, positiveFunction_, and target_.

MeanVarianceFromTarget() [3/3]

template<class Real>

ROL::MeanVarianceFromTarget< Real >::MeanVarianceFromTarget ( ROL::ParameterList & parlist )

inline

Constructor.

Parameters

[in]

parlist

is a parameter list specifying inputs

parlist should contain sublists "SOL"->"Risk Measure"->"Mean Plus Variance From Target" and within the "Mean Plus Variance From Target" sublist should have the following parameters

• "Targets" (array of scalars)
• "Orders" (array of unsigned integers)
• "Coefficients" (array of positive scalars)
• "Deviation Type" (eighter "Upper" or "Absolute")
• A sublist for positive function information.

Definition at line 143 of file ROL_MeanVarianceFromTarget.hpp.

References checkInputs(), coeff_, NumMoments_, order_, positiveFunction_, and target_.

Member Function Documentation

checkInputs()

template<class Real>

void ROL::MeanVarianceFromTarget< Real >::checkInputs ( void ) const

inlineprivate

Definition at line 66 of file ROL_MeanVarianceFromTarget.hpp.

References coeff_, order_, positiveFunction_, and zero.

Referenced by MeanVarianceFromTarget(), MeanVarianceFromTarget(), and MeanVarianceFromTarget().

updateValue()

template<class Real>

void ROL::MeanVarianceFromTarget< Real >::updateValue ( Objective< Real > & obj, const Vector< Real > & x, const std::vector< Real > & xstat, Real & tol )

inline

Definition at line 169 of file ROL_MeanVarianceFromTarget.hpp.

References coeff_, NumMoments_, order_, positiveFunction_, and target_.

updateGradient()

template<class Real>

void ROL::MeanVarianceFromTarget< Real >::updateGradient ( Objective< Real > & obj, const Vector< Real > & x, const std::vector< Real > & xstat, Real & tol )

inline

Definition at line 183 of file ROL_MeanVarianceFromTarget.hpp.

References coeff_, NumMoments_, order_, positiveFunction_, and target_.

updateHessVec()

template<class Real>

void ROL::MeanVarianceFromTarget< Real >::updateHessVec ( Objective< Real > & obj, const Vector< Real > & v, const std::vector< Real > & vstat, const Vector< Real > & x, const std::vector< Real > & xstat, Real & tol )

inline

Definition at line 199 of file ROL_MeanVarianceFromTarget.hpp.

References coeff_, NumMoments_, order_, positiveFunction_, and target_.

Member Data Documentation

positiveFunction_

template<class Real>

ROL::Ptr<PositiveFunction<Real> > ROL::MeanVarianceFromTarget< Real >::positiveFunction_

private

Definition at line 46 of file ROL_MeanVarianceFromTarget.hpp.

Referenced by checkInputs(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), updateGradient(), updateHessVec(), and updateValue().

target_

template<class Real>

std::vector<Real> ROL::MeanVarianceFromTarget< Real >::target_

private

Definition at line 47 of file ROL_MeanVarianceFromTarget.hpp.

Referenced by MeanVarianceFromTarget(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), updateGradient(), updateHessVec(), and updateValue().

order_

template<class Real>

std::vector<Real> ROL::MeanVarianceFromTarget< Real >::order_

private

Definition at line 48 of file ROL_MeanVarianceFromTarget.hpp.

Referenced by checkInputs(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), updateGradient(), updateHessVec(), and updateValue().

coeff_

template<class Real>

std::vector<Real> ROL::MeanVarianceFromTarget< Real >::coeff_

private

Definition at line 49 of file ROL_MeanVarianceFromTarget.hpp.

Referenced by checkInputs(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), updateGradient(), updateHessVec(), and updateValue().

NumMoments_

template<class Real>

uint ROL::MeanVarianceFromTarget< Real >::NumMoments_

private

Definition at line 50 of file ROL_MeanVarianceFromTarget.hpp.

Referenced by MeanVarianceFromTarget(), MeanVarianceFromTarget(), MeanVarianceFromTarget(), updateGradient(), updateHessVec(), and updateValue().

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The documentation for this class was generated from the following file:

• ROL_MeanVarianceFromTarget.hpp