I have uploaded the MATLAB implementation of the Bayesian LASSO sampling hierarchy for inference of autoregressive models from an observed time series. The idea behind the approach is place Laplace prior distributions over the partial autocorrelations of an AR(k) model, which leads to a relatively simple Gibbs’ sampling scheme, and guarantees stationarity. Both empirical Bayes and fully Bayesian estimation of the shrinkage hyperparameter is available.
Once downloaded and extracted from the ZIP file, all 3 folders/subfolders should be added to the MATLAB path. The script “RunRealDataTest” demonstrates how to use the software. [code]
- “Estimation of Stationary Autoregressive Models with the Bayesian LASSO”, D. F. Schmidt and E. Makalic, Journal of Time Series Analysis, Vol. 34, No. 5, pp. 517–531, 2013