Array of correlated 1-D stochastic processes More...

#include <stochasticprocessarray.hpp>

Inheritance diagram for StochasticProcessArray:

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Public Member Functions
	StochasticProcessArray (const std::vector< ext::shared_ptr< StochasticProcess1D > > &, const Matrix &correlation)

Size	size () const override
	returns the number of dimensions of the stochastic process More...

Array	initialValues () const override
	returns the initial values of the state variables More...

Array	drift (Time t, const Array &x) const override
	returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \) More...

Array	expectation (Time t0, const Array &x0, Time dt) const override

Matrix	diffusion (Time t, const Array &x) const override
	returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \) More...

Matrix	covariance (Time t0, const Array &x0, Time dt) const override

Matrix	stdDeviation (Time t0, const Array &x0, Time dt) const override

Array	apply (const Array &x0, const Array &dx) const override

Array	evolve (Time t0, const Array &x0, Time dt, const Array &dw) const override

Time	time (const Date &) const override

const ext::shared_ptr< StochasticProcess1D > &	process (Size i) const

Matrix	correlation () const

Public Member Functions inherited from StochasticProcess
	~StochasticProcess () override=default

virtual Size	factors () const
	returns the number of independent factors of the process More...

void	update () override

Public Member Functions inherited from Observer
	Observer ()=default

	Observer (const Observer &)

Observer &	operator= (const Observer &)

virtual	~Observer ()

std::pair< iterator, bool >	registerWith (const ext::shared_ptr< Observable > &)

void	registerWithObservables (const ext::shared_ptr< Observer > &)

Size	unregisterWith (const ext::shared_ptr< Observable > &)

void	unregisterWithAll ()

virtual void	update ()=0

virtual void	deepUpdate ()

Public Member Functions inherited from Observable
	Observable ()

	Observable (const Observable &)

Observable &	operator= (const Observable &)

	Observable (Observable &&)=delete

Observable &	operator= (Observable &&)=delete

virtual	~Observable ()=default

void	notifyObservers ()

Protected Attributes
std::vector< ext::shared_ptr< StochasticProcess1D > >	processes_

Matrix	sqrtCorrelation_

Protected Attributes inherited from StochasticProcess
ext::shared_ptr< discretization >	discretization_

Additional Inherited Members
Public Types inherited from Observer
typedef set_type::iterator	iterator

Protected Member Functions inherited from StochasticProcess
	StochasticProcess ()=default

	StochasticProcess (ext::shared_ptr< discretization >)

Detailed Description

Array of correlated 1-D stochastic processes

Definition at line 35 of file stochasticprocessarray.hpp.

Constructor & Destructor Documentation

◆ StochasticProcessArray()

StochasticProcessArray	(	const std::vector< ext::shared_ptr< StochasticProcess1D > > &	processes,
		const Matrix &	correlation
	)

Definition at line 26 of file stochasticprocessarray.cpp.

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Member Function Documentation

◆ size()

Size size ( ) const

overridevirtual

returns the number of dimensions of the stochastic process

Implements StochasticProcess.

Definition at line 42 of file stochasticprocessarray.cpp.

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◆ initialValues()

Array initialValues ( ) const

overridevirtual

returns the initial values of the state variables

Implements StochasticProcess.

Definition at line 46 of file stochasticprocessarray.cpp.

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◆ drift()

Array drift	(	Time	t,
		const Array &	x
	)		const

overridevirtual

returns the drift part of the equation, i.e., \( \mu(t, \mathrm{x}_t) \)

Implements StochasticProcess.

Definition at line 53 of file stochasticprocessarray.cpp.

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◆ expectation()

Array expectation	(	Time	t0,
		const Array &	x0,
		Time	dt
	)		const

overridevirtual

returns the expectation \( E(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) of the process after a time interval \( \Delta t \) according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Definition at line 73 of file stochasticprocessarray.cpp.

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◆ diffusion()

Matrix diffusion	(	Time	t,
		const Array &	x
	)		const

overridevirtual

returns the diffusion part of the equation, i.e. \( \sigma(t, \mathrm{x}_t) \)

Implements StochasticProcess.

Definition at line 61 of file stochasticprocessarray.cpp.

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◆ covariance()

Matrix covariance	(	Time	t0,
		const Array &	x0,
		Time	dt
	)		const

overridevirtual

returns the covariance \( V(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) of the process after a time interval \( \Delta t \) according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Definition at line 95 of file stochasticprocessarray.cpp.

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◆ stdDeviation()

Matrix stdDeviation	(	Time	t0,
		const Array &	x0,
		Time	dt
	)		const

overridevirtual

returns the standard deviation \( S(\mathrm{x}_{t_0 + \Delta t} | \mathrm{x}_{t_0} = \mathrm{x}_0) \) of the process after a time interval \( \Delta t \) according to the given discretization. This method can be overridden in derived classes which want to hard-code a particular discretization.

Reimplemented from StochasticProcess.

Definition at line 82 of file stochasticprocessarray.cpp.

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