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sstvars: Structural Smooth Transition Vector Autoregressive Models R2 months ago
Introduction | Introduction | Smooth Transition Vector Autoregressive Models | Smooth Transition Vector Autoregressive Models | Structural STVAR models | Structural STVAR models | Estimation | Estimation | Testing parameter constraints | Testing parameter constraints | Residual based model diagnostics | Residual based model diagnostics | Impulse response analysis | Impulse response analysis | Historical decompositions | Historical decompositions | Counterfactual analysis | Counterfactual analysis | Building a STVAR model with specific parameter values | Building a STVAR model with specific parameter values | Simulation and forecasting | Simulation and forecasting | Summary | Summary | A table of some useful functions | References
uGMAR: A Family of Mixture Autoregressive Models in R9 months ago
gmvarkit: A Family of Mixture Vector Autoregressive Models in R9 months ago
Introduction | Introduction | Models | Models | Estimation | Estimation | Quantile residual based model diagnostics | Quantile residual based model diagnostics | Impulse response analysis | Impulse response analysis | Building a GSMVAR model with specific parameter values | Simulation and forecasting | Simulation and forecasting | Summary | Summary | Computational details | A table of some useful functions | References | Properties of multivariate Gaussian and Student's t distribution | Appendix A: Properties of multivariate Gaussian and Student's t distribution | Quantile residuals of the G-StMVAR model | Appendix B: Quantile residuals of the G-StMVAR model | Monte Carlo algorithm for estimating the GIRF | Appendix C: Monte Carlo algorithm for estimating the GIRF