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Birnbaum-Saunders Quantile Regression Models with Application to Spatial Data

Luis Sánchez (), Víctor Leiva (), Manuel Galea () and Helton Saulo ()
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Luis Sánchez: Department of Mathematics and Statistics, Universidad de La Frontera, Temuco 4780000, Chile
Víctor Leiva: School of Industrial Engineering, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362807, Chile
Manuel Galea: Department of Statistics, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile
Helton Saulo: Department of Statistics, Universidade de Brasília, Brasília 70910-90, Brazil

Mathematics, 2020, vol. 8, issue 6, 1-17

Abstract: In the present paper, a novel spatial quantile regression model based on the Birnbaum–Saunders distribution is formulated. This distribution has been widely studied and applied in many fields. To formulate such a spatial model, a parameterization of the multivariate Birnbaum–Saunders distribution, where one of its parameters is associated with the quantile of the respective marginal distribution, is established. The model parameters are estimated by the maximum likelihood method. Finally, a data set is applied for illustrating the formulated model.

Keywords: data analytics; geostatistical models; maximum likelihood method; multivariate distributions; R software; statistical parameterizations (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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