Santos, Bruno R., Bolfarine, Heleno (2013) A two-part model using quantile regression under a Bayesian perspective. In: Proceedings of the 28th International Workshop on Statistical Modelling. . pp. 363-374. Statistical Modelling Society ISBN 978-88-96251-47-8. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:90495)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. |
Abstract
We develop an extension of the two-part model proposed by Cragg (1971) considering the asymmetric Laplace distribution for the continuous density, proposing a quantile regression analysis in the process, within a Bayesian approach. We also consider the case where there could be a zero inflation process while estimating a Bayesian tobit quantile regression, and by the imputation of the latent variable indicating whether a zero observation belongs to a point mass or the continuous distribution, we are able to obtain a generalization of our two-part model. We illustrate our method in a known data set in the field of econometrics.
| Item Type: | Conference or workshop item (Paper) |
|---|---|
| Uncontrolled keywords: | Bayesian quantile regression; Two-part model; MCMC |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
| Depositing User: | Amy Boaler |
| Date Deposited: | 30 Sep 2021 11:54 UTC |
| Last Modified: | 16 Nov 2021 10:27 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/90495 (The current URI for this page, for reference purposes) |
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