uGASSim-class function

Class for Univariate GAS Simulation

Class for Univariate GAS model Simulation. 0.1

class

Objects from the Class

A virtual Class: No objects may be created from it.

Slots

• ModelInfo:: Object of class list. Contains information about the univariate GAS specification:

    * `iT` `numeric` Time length of simulated observations.
    * `iK` `numeric` Number of (possibly) time-varying parameters implied by the distributional assumption.
    * `vKappa` `numeric` Vector of unconditional level for the reparametrised vector of parameters.
    * `mA` `matrix` Of coefficients of dimension iK x iK that premultiply the conditional score in the GAS updating recursion.
    * `mB` `matrix` Of autoregressive coefficients of dimension iK x iK.
    * `Dist` `character` Label of the conditional distribution, see DistInfo
    * `ScalingType` `character` Representing the scaling mechanism for the conditional score, see DistInfo .
  

• GASDyn:: Object of class list. Contains: the series of simulated parameters (GASDyn$mTheta), the series of scaled scores (GASDyn$mInnovation), the series of unrestricted simulated parameters (GASDyn$mTheta_tilde), the series of log densities (GASDyn$vLLK), the log likelihood evaluated at its optimum value (GASDyn$dLLK).

• Data:: Object of class numeric. Vector of length iT of simulated data.

Methods

• show signature(object = 'uGASSim'): Show summary.
• plot signature(x = 'uGASSim', y = 'missing'): Plot simulated data and parameters.
• getFilteredParameters signature(object = 'uGASSim'): Extract simulated parameters.
• getObs signature(object = 'uGASSim'): Extract simulated observations.
• coef signature(object = 'uGASSim'): Extract delivered coefficients.
• quantile signature(object = 'uGASSim'): Compute quantiles of the filtered simulated density at each point in time. It accepts the additional argument probs representing the vector of probabilities.
• ES signature(object = 'uGASSim'): Compute the Expected Shortfall of the filtered simulated density at each point in time. It accepts the additional argument probs representing the vector of probabilities.

Author(s)

Leopoldo Catania