A Bayesian estimation of lag lengths in distributed lag models
| Autor: | Rubiane M. Pires, José Galvão Leite, Camila Pedrozo Rodrigues, Carlos R. Diniz |
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| Rok vydání: | 2012 |
| Předmět: | |
| Zdroj: | Journal of Statistical Computation and Simulation. 84:415-427 |
| ISSN: | 1563-5163 0094-9655 |
| DOI: | 10.1080/00949655.2012.712972 |
| Popis: | Dynamic regression models are widely used because they express and model the behaviour of a system over time. In this article, two dynamic regression models, the distributed lag (DL) model and the autoregressive distributed lag model, are evaluated focusing on their lag lengths. From a classical statistics point of view, there are various methods to determine the number of lags, but none of them are the best in all situations. This is a serious issue since wrong choices will provide bad estimates for the effects of the regressors on the response variable. We present an alternative for the aforementioned problems by considering a Bayesian approach. The posterior distributions of the numbers of lags are derived under an improper prior for the model parameters. The fractional Bayes factor technique [A. O'Hagan, Fractional Bayes factors for model comparison (with discussion), J. R. Statist. Soc. B 57 (1995), pp. 99–138] is used to handle the indeterminacy in the likelihood function caused by the improper prio... |
| Databáze: | OpenAIRE |
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