Birnbaum-Saunders Quantile Regression Models with Application to Spatial Data

Clicks: 173
ID: 271107
2020
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
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.
Reference Key
sánchez2020mathematicsbirnbaum-saunders Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Luis Sánchez;Víctor Leiva;Manuel Galea;Helton Saulo;Sánchez, Luis;Leiva, Víctor;Galea, Manuel;Saulo, Helton;
Journal Mathematics
Year 2020
DOI
10.3390/math8061000
URL
https://www.mdpi.com/2227-7390/8/6/1000
Keywords
data analytics r software geostatistical models maximum likelihood method multivariate distributions statistical parameterizations

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.