Geostatistical mixed beta regression: a Bayesian approach
Impacto
Scholar |
Otros documentos de la autoría: Lagos Álvarez, Bernardo M.; Fustos Toribio, Roberto Miguel; Figueroa Zúñiga, Jorge; Mateu, Jorge
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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http://dx.doi.org/10.1007/s00477-016-1308-5 |
Metadatos
Título
Geostatistical mixed beta regression: a Bayesian approachAutoría
Fecha de publicación
2017Editor
Springer VerlagCita bibliográfica
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), 571-584Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s00477-016-1308-5Palabras clave / Materias
Resumen
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. [-]
Publicado en
Stochastic Environmental Research and Risk Assessment, 2017, vol. 31, núm. 2Derechos de acceso
© Springer-Verlag Berlin Heidelberg 2016
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