Geostatistical mixed beta regression: a Bayesian approach
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Other documents of the author: Lagos Álvarez, Bernardo M.; Fustos Toribio, Roberto Miguel; Figueroa Zúñiga, Jorge; Mateu, Jorge
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http://dx.doi.org/10.1007/s00477-016-1308-5 |
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Title
Geostatistical mixed beta regression: a Bayesian approachAuthor (s)
Date
2017Publisher
Springer VerlagBibliographic 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), 571-584Type
info:eu-repo/semantics/articlePublisher version
https://link.springer.com/article/10.1007/s00477-016-1308-5Subject
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 ... [+]
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. [-]
Is part of
Stochastic Environmental Research and Risk Assessment, 2017, vol. 31, núm. 2Rights
© Springer-Verlag Berlin Heidelberg 2016
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