Bayesian Modeling of Autoregressive Threshold Time Series Models
Identify the autoregressive orders for a log-normal TAR model given th...
Identify the autoregressive orders for a Gaussian TAR model given the ...
Estimate a log-normal TAR model using Least Square method given the st...
Estimate a Gaussian TAR model using Least Square method given the stru...
Estimate a TAR model using Gibbs Sampler given the structural paramete...
Estimate a Gaussian TAR model using Gibbs Sampler given the structural...
Identify the number of regimes and the corresponding thresholds for a ...
Identify the number of regimes and the corresponding thresholds for a ...
Simulate a series from a log-normal TAR model with Gaussian distribute...
Simulate a series from a TAR model with Gaussian distributed error.
Identification and estimation of the autoregressive threshold models with Gaussian noise, as well as positive-valued time series. The package provides the identification of the number of regimes, the thresholds and the autoregressive orders, as well as the estimation of remain parameters. The package implements the methodology from the 2005 paper: Modeling Bivariate Threshold Autoregressive Processes in the Presence of Missing Data <DOI:10.1081/STA-200054435>.