The FCVAR package estimates the Fractionally Cointegrated Vector Autoregressive (VAR) model. It includes functions for lag selection, cointegration rank selection and hypothesis testing.
Functions in the FCVAR package are divided into four categories: Estimation, Postestimation, Specification and Auxiliary functions.
NULL. Object included for description only.
The estimation functions include the primary estimation function
and associated functions to set estimation options and display results.
Some of these functions define, modify and test the user-specified options for estimation.
FCVARoptions defines the default estimation options used in the FCVAR
estimation procedure and the related programs.
The user can then revise the options such as the settings for optimization and
restrictions for testing hypotheses.
After making these changes, an internal function
FCVARoptionUpdates sets and tests
estimation options for validity and compatibility.
The postestimation functions are used to display summary statistics, test hypotheses and test the goodness of fit of the estimated model. These include:
for a likelihood ratio test of a restricted vs. an unrestricted model
for generating a distribution of a likelihood ratio test statistic
for calculating recursive forecasts with the FCVAR model
The specification functions are used to estimate a series of models in order to make model specfication decisions. These include:
for selection of the lag order
for choosing the cointegrating rank
for generating a distribution of a likelihood ratio test statistic for the rank test
The auxiliary functions are used to perform intermediate calculations for estimation. These functions are mainly designed for use only within the estimation function. Some exceptions include:
for fractionally differencing a multivariate series
for generating bootstrap samples from the FCVAR model
for performing a grid-search optimization with the FCVAR likelihood function
votingJNP2014 is included for examples of the model building process.
Sample model builds with hypothesis tests and examples of other extensions are found
in the example script
See FCVAR_README.pdf for details
and also see
for more information about estimating the FCVAR model.
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