vgxdisp

Display VARMAX model parameters and statistics

Syntax

vgxdisp(Spec)
vgxdisp(SpecStd)
vgxdisp(Spec,SpecStd)
vgxdisp(Spec1,Spec2)
vgxdisp(Spec1Std,Spec2Std)
vgxdisp(Spec1,Spec1Std,Spec2,Spec2Std)
vgxdisp(Spec1,Spec2,Spec1Std,Spec2Std)
vgxdisp(Spec1,Spec1Std,Spec2,Spec2Std,...,Specn,SpecnStd)
vgxdisp(Spec1,Spec2,...,Specn,Spec1Std,Spec2Std,...,SpecnStdn)
vgxdisp(___,'Name1',Value1,'Name2',Value2,...)

Description

vgxdisp displays multivariate time series model parameters and standard errors in different formats.

  • vgxdisp(Spec) displays a single specification structure Spec.

  • vgxdisp(SpecStd) displays a single standard-error structure SpecStd with no t-statistics.

  • vgxdisp(Spec,SpecStd) displays a single specification structure SpecStd with standard errors.

  • vgxdisp(Spec1,Spec2) displays two specification structures Spec1 and Spec2 side-by-side. This option displays the specification structures in table format only.

  • vgxdisp(Spec1Std,Spec2Std) displays two standard-error structures Spec1Std and Spec2Std side-by-side. This option displays the standard-error structures in table format only.

  • vgxdisp(Spec1,Spec1Std,Spec2,Spec2Std) displays two specification structures side-by-side with standard errors. This option displays the specification structures in table format only.

  • vgxdisp(Spec1,Spec2,Spec1Std,Spec2Std) also displays two specification structures side-by-side with standard errors. This option displays the specification structures in table format only.

  • vgxdisp(Spec1,Spec1Std,Spec2,Spec2Std,...,Specn,SpecnStd) displays n specification structures with standard errors. This option displays the specification structures in table format only.

  • vgxdisp(Spec1,Spec2,...,Specn,Spec1Std,Spec2Std,...,SpecnStdn) displays n specification structures with standard errors. This option displays the specification structures in table format only.

  • vgxdisp(___,'Name1',Value1,'Name2',Value2,...) displays specification structures with additional with additional options specified by one or more Name,Value pair arguments.

Required Input Arguments

Spec

A multivariate time series specification structure for an n-dimensional time series process, as created by vgxset.

SpecStd

A multivariate time series specification structure that contains standard errors (or estimation errors) of estimated parameters for a companion n-dimensional time series process, as created by vgxset. Since the standard errors are maximum likelihood estimates, set the parameter DoFAdj to true to apply a degree-of-freedom adjustment and report ordinary least squares estimates.

If you input multiple specification structures, all must have the same dimension n. Pairs of specification structures and standard errors must be conformable. You can, however, specify different AR or MA lag structures for multiple specification structures, and if the inputs are exogenous, you can also specify different numbers of parameters.

If the specification structures do not set any logical indicators for model parameter estimation ("solve" information), vgxdisp assumes that every parameter is available for estimation. In this case, the degree-of-freedom adjustment that vgxdisp makes is the most conservative estimate for standard errors.

Optional Input Arguments

Specify the following optional input arguments as variable-length lists of matching parameter name/value pairs: 'Name1', Value1, 'Name2', Value2, ... and so on. The following rules apply when specifying parameter-name pairs:

  • Specify the parameter name as a character string, followed by its corresponding parameter value.

  • You can specify parameter name/value pairs in any order.

  • Parameter names are case insensitive.

  • You can specify unambiguous partial string matches.

The following table lists valid parameter names.

DoFAdj

Specifies whether vgxdisp adjusts for degrees of freedom in standard errors. Options are:

  • truevgxdisp applies degree-of-freedom adjustment (least-squares estimation).

  • falsevgxdisp does not apply degree-of-freedom adjustment (maximum likelihood estimation).

Format

Specifies format in which model parameters and standard errors are displayed. Options are:

  • 'equation'vgxdisp displays model parameters and standard errors in canonical equation form. This is the default format for single models.

  • 'table'vgxdisp displays model parameters and standard errors in tabular form. This is the only option for multiple models.

Examples

expand all

Display VAR Models

Start with a 2-dimensional VARMA(2,2) data and display the specification Spec:

load Data_VARMA22

vgxdisp(Spec);
  Model  : 2-D VARMA(2,2) with No Additive Constant
           Conditional mean is AR-stable and is MA-invertible
  AR(1) Autoregression Matrix:
        0.373935       0.124043 
        0.375488       0.259077 
  AR(2) Autoregression Matrix:
       0.0754758     -0.0972418 
       0.0687406      0.0155532 
  MA(1) Moving Average Matrix:
        0.205242      -0.239925 
      -0.0881847     -0.0617094 
  MA(2) Moving Average Matrix:
      -0.0682232      0.0107276 
       -0.155213     -0.0040213 
  Q Innovations Covariance:
            0.08           0.01 
            0.01           0.03 

Assume that you have a 2-dimensional VAR(2) approximation of the original VARMA(2, 2) model estimated from time series data that is in the specification structure EstSpec:

vgxdisp(Spec, EstSpec);
  Model 1: 2-D VARMA(2,2) with No Additive Constant
           Conditional mean is AR-stable and is MA-invertible
  Model 2: 2-D VAR(2) with No Additive Constant
           Conditional mean is AR-stable and is MA-invertible
       Parameter        Model 1        Model 2
  -------------- -------------- --------------
      AR(1)(1,1)       0.373935       0.850166 
           (1,2)       0.124043     -0.0498191 
           (2,1)       0.375488       0.219381 
           (2,2)       0.259077     -0.0227752 
      AR(2)(1,1)      0.0754758      -0.294609 
           (1,2)     -0.0972418       0.221336 
           (2,1)      0.0687406       0.264504 
           (2,2)      0.0155532      0.0819125 
      MA(1)(1,1)       0.205242                
           (1,2)      -0.239925                
           (2,1)     -0.0881847                
           (2,2)     -0.0617094                
      MA(2)(1,1)     -0.0682232                
           (1,2)      0.0107276                
           (2,1)      -0.155213                
           (2,2)     -0.0040213                
          Q(1,1)           0.08       0.051844 
          Q(2,1)           0.01     0.00711775 
          Q(2,2)           0.03      0.0286081 
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