ARMA-GARCH/APARCH Models with Stable, GEV and GAt Innovations
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Documentation for package ‘GEVStableGarch’ version 2.0.0
Help Pages
| coef.gs_fit | Methods for fitted models |
| dgat | Generalized Asymmetric t (GAT) Distribution |
| fitted.gs_fit | Methods for fitted models |
| GAT | Generalized Asymmetric t (GAT) Distribution |
| gat | Generalized Asymmetric t (GAT) Distribution |
| gs_aparch_moment | APARCH moment of the innovation distribution |
| gs_bootstrap | Parametric bootstrap standard errors and confidence intervals |
| gs_check_dist | Self check of an innovation distribution |
| gs_dist | Innovation distribution for ARMA-GARCH/APARCH models |
| gs_fit | Fit an ARMA-GARCH/APARCH model by maximum likelihood |
| gs_fit-methods | Methods for fitted models |
| gs_gat | GAt innovations |
| gs_gev | GEV innovations |
| gs_model | Set the parameters of an ARMA-GARCH/APARCH model |
| gs_sim | Simulate an ARMA-GARCH/APARCH model |
| gs_spec | Specify an ARMA-GARCH/APARCH model |
| gs_stable | Stable innovations (S0 parametrization) |
| gs_stationarity | Persistence of the APARCH scale recursion |
| logLik.gs_fit | Methods for fitted models |
| nobs.gs_fit | Methods for fitted models |
| pgat | Generalized Asymmetric t (GAT) Distribution |
| predict.gs_fit | Forecast an ARMA-GARCH/APARCH model |
| predict.gs_model | Forecast an ARMA-GARCH/APARCH model |
| print.gs_fit | Methods for fitted models |
| qgat | Generalized Asymmetric t (GAT) Distribution |
| residuals.gs_fit | Methods for fitted models |
| rgat | Generalized Asymmetric t (GAT) Distribution |
| sigma.gs_fit | Methods for fitted models |
| summary.gs_fit | Methods for fitted models |
| vcov.gs_fit | Methods for fitted models |