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Geostatistical mixed beta regression: a Bayesian approach
dc.contributor.author | Lagos Álvarez, Bernardo M. | |
dc.contributor.author | Fustos Toribio, Roberto Miguel | |
dc.contributor.author | Figueroa Zúñiga, Jorge | |
dc.contributor.author | Mateu, Jorge | |
dc.date.accessioned | 2017-06-09T18:37:35Z | |
dc.date.available | 2017-06-09T18:37:35Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Lagos-Álvarez, B. M., Fustos-Toribio, R., Figueroa-Zúñiga, J., & Mateu, J. (2017). Geostatistical mixed beta regression: a Bayesian approach. Stochastic Environmental Research and Risk Assessment, 31(2), 571-584 | ca_CA |
dc.identifier.uri | http://hdl.handle.net/10234/167945 | |
dc.description.abstract | This paper develops regression techniques for geostatistical data, with an emphasis in proportions mea- sured on a continuous scale. Specifically, it deals with Beta regression models with mixed effects to control the spatial variability from a Bayesian approach. We use a suit- able parametrization of the Beta distribution in terms of its mean and the precision parameter, allowing for both parameters to be modeled through regression structures that may involve fixed and random effects. Specification of prior distributions is discussed, computational implemen- tation via Gibbs sampling is provided, and the methodol- ogy is illustrated using simulated and real data. | ca_CA |
dc.description.sponsorShip | The authors would like to acknowledge the fol- lowing partial financial support. The first author thanks the VRID grant 216.014.026-1.0, from University of Concepcio ́ n. The second author thanks the Fondecyt grant 11130483, and the third author the Advanced Mining Technology Center, University of Chile and CSIRO-Chile for having provided the facilities and equipment in which the data were simulated. Finally, the fourth author thanks the grants MTM2013-43917-P from the Spanish Ministry of Science and Education, and P1-1B2015-40. | ca_CA |
dc.format.extent | 14 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Springer Verlag | ca_CA |
dc.relation.isPartOf | Stochastic Environmental Research and Risk Assessment, 2017, vol. 31, núm. 2 | ca_CA |
dc.rights | © Springer-Verlag Berlin Heidelberg 2016 | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | Bayesian analysis | ca_CA |
dc.subject | Beta distribution | ca_CA |
dc.subject | Beta regression | ca_CA |
dc.subject | Mixed effects | ca_CA |
dc.subject | Proportions | ca_CA |
dc.title | Geostatistical mixed beta regression: a Bayesian approach | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | http://dx.doi.org/10.1007/s00477-016-1308-5 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://link.springer.com/article/10.1007/s00477-016-1308-5 | ca_CA |
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