vector autoregressive model, fittable by method of moments only (Yule-Walker eqns) More...

Inheritance diagram for CronoSeries.TimeSeries.Models.VARModel:

Public Member Functions
	VARModel (int order, int dimension)

void	FitByMethodOfMoments ()
	For multivariate autoregressive models, we just solve the Yule-Walker equations to estimate parameters. This is conceptually straightforward (see any standard textbook), but requires a lot of linear algebra book-keeping. More...

override string	GetShortDescription ()

override string	GetParameterName (int index)

override string	GetParameterDescription (int index)

override int	NumOutputs ()

override object	GetOutput (int socket)

override string	GetOutputName (int index)

override double	LogLikelihood (Vector< double > parameter, double penaltyFactor, bool fillOutputs)
	Returns the (possibly penalized) log-likelihood of the model with specified parameters and the current object theData. If parameter==null, it will use CURRENT parameters. If fillOutputs is true, then the residuals and any other outputs will be filled in. More...

override Data.TimeSeries	SimulateData (List< DateTime > inputs, int randomSeed)
	This function must simulate from the current model. More...

override object	BuildForecasts (object otherData, object inputs)
	This function generates forecasts (or fitted values) for the specified inputs, based on the existing data object and current model parameters. Results are returned in a form that depends on the model, for example, as a TimeSeries of DistributionSummary objects More...

override List< Type >	GetOutputTypesFor (int socket)

Public Member Functions inherited from CronoSeries.TimeSeries.Models.MVTimeSeriesModel
override List< Type >	GetAllowedInputTypesFor (int socket)

Public Member Functions inherited from CronoSeries.TimeSeries.Models.TimeSeriesModel
override int	NumInputs ()

override string	GetInputName (int socket)

override bool	InputIsFree (int socket)

override bool	SetInput (int socket, object item, StringBuilder failMsg)

override List< Type >	GetAllowedInputTypesFor (int socket)

Public Member Functions inherited from CronoSeries.TimeSeries.Models.Model
string	GetDescription ()

bool	CanUseMLE ()

bool	CanUseMoM ()

bool	CanHandleNaNs ()

virtual void	FitByMLE (int numIterationsLDS, int numIterationsOpt, double consistencyPenalty, Optimizer.OptimizationCallback optCallback)

virtual void	FitByMoM ()
	Fits model by method of moments. This is the default method used of CanUseMLE is false. More...

bool	InputToOutputIsValid ()

bool	SetParameters (Vector< double > v)

Protected Member Functions
override bool	CheckParameterValidity (Vector< double > param)
	Checks for validity of parameters. More...

override Vector< double >	ComputeConsequentialParameters (Vector< double > parameter)
	This function must fill in values of consequential parameters. These parameters are determined by the current ParameterState[] settings in ParameterStates. These can depend on the non-consequential parameters and the data set. The function should throw an exception if it is not possible. The parameter vector with parameters filled in should be returned. More...

override void	OnDataConnection ()
	This function is called immediately after a data object is connected to the model. Any initial processing (e.g. determining dimension of parameter vector, etc.) should be done here. More...

override void	InitializeParameters ()
	This function is called after OnDataConnection. It can assume valid data is available, and it must fill in valid default parameter values. It typically also sets default parameter states, for purposes of estimation. More...

Protected Member Functions inherited from CronoSeries.TimeSeries.Models.MVTimeSeriesModel
override bool	CheckDataValidity (object data, StringBuilder failMessage)
	This function checks to see if the object can be cast into the appropriate form for the model. More...

Protected Member Functions inherited from CronoSeries.TimeSeries.Models.Model
double	NegativeLogLikelihood (Vector< double > partialCube)
	This function is a wrapper for another function, to be passed to a minimizer. More...

Protected Attributes
Vector< double >	mu

int	order

Matrix< double >[]	Phi

Matrix< double >	Sigma

int	NumParameters => dimension + dimension * dimension * (order + 1)

Protected Attributes inherited from CronoSeries.TimeSeries.Models.MVTimeSeriesModel
int	dimension

MVTimeSeries	mvts

Properties
override string	Description `[get]`

override Vector< double >	Parameters `[get, set]`

Properties inherited from CronoSeries.TimeSeries.Models.MVTimeSeriesModel
int	Dimension `[get, protected set]`

Properties inherited from CronoSeries.TimeSeries.Models.TimeSeriesModel
override Vector< double >	Parameters `[get, set]`

Properties inherited from CronoSeries.TimeSeries.Models.Model
abstract string	Description `[get]`
	Should return a description of the model, including current parameter values if desired. More...

object	Residuals `[get, protected set]`

object	TheData `[get, set]`

double	GoodnessOfFit `[get, protected set]`

abstract Vector< double >	Parameters `[get, set]`

ParameterState[]	ParameterStates `[get, set]`

string	ToolTipText `[get, set]`

Properties inherited from CronoSeries.TimeSeries.Data.IConnectable
string	ToolTipText `[get, set]`

Additional Inherited Members
Public Types inherited from CronoSeries.TimeSeries.Models.Model
enum	ParameterState { Free, Locked, Consequential }

Public Attributes inherited from CronoSeries.TimeSeries.Models.Model
object	theData

Static Protected Member Functions inherited from CronoSeries.TimeSeries.Models.Model
static Vector< double >	CubeFix (Vector< double > cube)
	This function makes sure that its vector argument really does contain an element of the unit hypercube. If not, it is mapped back to an element on the hypercube (the mapping is continuous). More...

Detailed Description

vector autoregressive model, fittable by method of moments only (Yule-Walker eqns)

Member Function Documentation

◆ BuildForecasts()

override object CronoSeries.TimeSeries.Models.VARModel.BuildForecasts	(	object	otherData,
		object	inputs
	)

inlinevirtual

This function generates forecasts (or fitted values) for the specified inputs, based on the existing data object and current model parameters. Results are returned in a form that depends on the model, for example, as a TimeSeries of DistributionSummary objects

Parameters

otherData
inputs	may have different interpretations, for time series, it is typically an IList of DateTime objects

Returns: a model-dependent object: for example, a time series of distribution summaries

Implements CronoSeries.TimeSeries.Models.Model.

◆ CheckParameterValidity()

override bool CronoSeries.TimeSeries.Models.VARModel.CheckParameterValidity ( Vector< double > param )

inlineprotectedvirtual

Checks for validity of parameters.

Parameters

param

Returns

Implements CronoSeries.TimeSeries.Models.Model.

◆ ComputeConsequentialParameters()

override Vector<double> CronoSeries.TimeSeries.Models.VARModel.ComputeConsequentialParameters ( Vector< double > parameter )

inlineprotectedvirtual

This function must fill in values of consequential parameters. These parameters are determined by the current ParameterState[] settings in ParameterStates. These can depend on the non-consequential parameters and the data set. The function should throw an exception if it is not possible. The parameter vector with parameters filled in should be returned.

Implements CronoSeries.TimeSeries.Models.Model.

◆ FitByMethodOfMoments()

void CronoSeries.TimeSeries.Models.VARModel.FitByMethodOfMoments ( )

inline

For multivariate autoregressive models, we just solve the Yule-Walker equations to estimate parameters. This is conceptually straightforward (see any standard textbook), but requires a lot of linear algebra book-keeping.

Implements CronoSeries.TimeSeries.Models.IMoMEstimable.

◆ InitializeParameters()

override void CronoSeries.TimeSeries.Models.VARModel.InitializeParameters ( )

inlineprotectedvirtual

This function is called after OnDataConnection. It can assume valid data is available, and it must fill in valid default parameter values. It typically also sets default parameter states, for purposes of estimation.

Implements CronoSeries.TimeSeries.Models.Model.

◆ LogLikelihood()

override double CronoSeries.TimeSeries.Models.VARModel.LogLikelihood	(	Vector< double >	parameter,
		double	penaltyFactor,
		bool	fillOutputs
	)

inlinevirtual

Returns the (possibly penalized) log-likelihood of the model with specified parameters and the current object theData. If parameter==null, it will use CURRENT parameters. If fillOutputs is true, then the residuals and any other outputs will be filled in.

Returns

Implements CronoSeries.TimeSeries.Models.Model.

◆ OnDataConnection()

override void CronoSeries.TimeSeries.Models.VARModel.OnDataConnection ( )

inlineprotectedvirtual

This function is called immediately after a data object is connected to the model. Any initial processing (e.g. determining dimension of parameter vector, etc.) should be done here.

Implements CronoSeries.TimeSeries.Models.Model.

◆ SimulateData()

override Data.TimeSeries CronoSeries.TimeSeries.Models.VARModel.SimulateData	(	List< DateTime >	dateTimes,
		int	randomSeed
	)

inlinevirtual

This function must simulate from the current model.

Parameters

dateTimes	these may have different interpretations, but for time series, is typically an IList of DateTime objects
randomSeed	random number seed

Returns

Implements CronoSeries.TimeSeries.Models.Model.

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

TimeSeries/Models/VARModel.cs

Public Member Functions

Protected Member Functions

Protected Attributes

Properties

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ BuildForecasts()

◆ CheckParameterValidity()

◆ ComputeConsequentialParameters()

◆ FitByMethodOfMoments()

◆ InitializeParameters()

◆ LogLikelihood()

◆ OnDataConnection()

◆ SimulateData()