Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach

Spatial data not only enables smart cities to visualize, analyze, and interpret data related to location and space, but also helps departments make more informed decisions. We apply a Bayesian quantile regression (BQR) of the partially linear varying coefficient spatial autoregressive (PLVCSAR) mode...

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Autori principali:	Rongshang Chen, Zhiyong Chen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2025-07-01
Serie:	Entropy
Soggetti:	spatial autoregressive models partially linear varying coefficient quantile regression Markov chain Monte Carlo approach Gibbs sampling
Accesso online:	https://www.mdpi.com/1099-4300/27/7/715
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