IRIS Toolbox Reference Manual

# Vector autoregressions (VAR) objects and functions

VAR objects can be constructed as plain VARs or simple panel VARs (with fixed effect), and estimated without or with prior dummy observations (quasi-bayesian VARs). VAR objects are reduced-form models; they are also the point of departure for identifying structural VARs (`SVAR` objects).

VAR methods:

#### Constructor

- `VAR` - Create new, empty reduced-form VAR object.

#### Getting information about VAR objects

- `addparam` - Add VAR parameters to a database (struct).
- `comment` - Get or set user comments in an IRIS object.
- `companion` - Matrices of first-order companion VAR.
- `eig` - Eigenvalues of a VAR process.
- `fprintf` - Write VAR model as formatted model code to text file.
- `get` - Query VAR object properties.
- `iscompatible` - True if two VAR objects can occur together on the LHS and RHS in an assignment.
- `isexplosive` - True if any eigenvalue is outside unit circle.
- `ispanel` - True for panel VAR based objects.
- `isstationary` - True if all eigenvalues are within unit circle.
- `length` - Number of alternative parameterisations in VAR object.
- `mean` - Mean of VAR process.
- `nfitted` - Number of data points fitted in VAR estimation.
- `rngcmp` - True if two VAR objects have been estimated using the same dates.
- `sprintf` - Print VAR model as formatted model code.
- `sspace` - Quasi-triangular state-space representation of VAR.
- `userdata` - Get or set user data in an IRIS object.

#### Referencing VAR objects

- `group` - Retrieve VAR object from panel VAR for specified group of data.
- `subsasgn` - Subscripted assignment for VAR objects.
- `subsref` - Subscripted reference for VAR objects.

#### Simulation, forecasting and filtering

- `ferf` - Forecast error response function.
- `filter` - Filter data using a VAR model.
- `forecast` - Unconditional or conditional VAR forecasts.
- `instrument` - Define conditioning instruments in VAR models.
- `resample` - Resample from a VAR object.
- `simulate` - Simulate VAR model.

#### Manipulating VARs

- `alter` - Expand or reduce the number of alternative parameterisations within a VAR object.
- `backward` - Backward VAR process.
- `demean` - Remove constant from VAR object.
- `horzcat` - Combine two compatible VAR objects in one object with multiple parameterisations.
- `integrate` - Integrate VAR process and data associated with it.

#### Stochastic properties

- `acf` - Autocovariance and autocorrelation functions for VAR variables.
- `fmse` - Forecast mean square error matrices.
- `vma` - Matrices describing the VMA representation of a VAR process.
- `xsf` - Power spectrum and spectral density functions for VAR variables.

#### Estimation, identification, and statistical tests

- `estimate` - Estimate a reduced-form VAR or BVAR.
- `infocrit` - Populate information criteria for a parameterised VAR.
- `lrtest` - Likelihood ratio test for VAR models.
- `portest` - Portmanteau test for autocorrelation in VAR residuals.
- `schur` - Compute and store triangular representation of VAR.

#### Getting on-line help on VAR functions

    help VAR
    help VAR/function_name

IRIS Toolbox. Copyright © 2007—2013 Jaromir Benes.