R: Bayesian Modeling of Autoregressive Threshold Time Series Models

# Bayesian Modeling of Autoregressive Threshold Time Series Models

## Documentation for package ‘TAR’ version 1.0

- DESCRIPTION file

## Help Pages

ARorder.lognorm | Identify the autoregressive orders for a log-normal TAR model given the number of regimes and thresholds.
ARorder.norm | Identify the autoregressive orders for a Gaussian TAR model given the number of regimes and thresholds.
LS.lognorm | Estimate a log-normal TAR model using Least Square method given the structural parameters.
LS.norm | Estimate a Gaussian TAR model using Least Square method given the structural parameters.
Param.lognorm | Estimate a TAR model using Gibbs Sampler given the structural parameters.
Param.norm | Estimate a Gaussian TAR model using Gibbs Sampler given the structural parameters.
reg.thr.lognorm | Identify the number of regimes and the corresponding thresholds for a log-normal TAR model.
reg.thr.norm | Identify the number of regimes and the corresponding thresholds for a Gaussian TAR model.
simu.tar.lognorm | Simulate a series from a log-normal TAR model with Gaussian distributed error for positive valued time series.
simu.tar.norm | Simulate a series from a TAR model with Gaussian distributed error.