Markov Chain Monte Carlo for Autologistic Regression Models with Application to the Distribution of Plant Species

In this paper, we explore using autologistic regression models for spatial binary data with covariates. Autologistic regression models can handle binary responses exhibiting both spatial correlation and dependence on covariates. We use Markov chain Monte Carlo (MCMC) to estimate the parameters in th...

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Veröffentlicht in:	Biometrics 1998-06, Vol.54 (2), p.509-524
Hauptverfasser:	Huffer, Fred W., Wu, Hulin
Format:	Artikel
Sprache:	eng
Schlagworte:	Climate models Confidence interval Markov chains Maximum likelihood estimation Parametric models Regression analysis Sample size Spatial models Standard deviation Statistical variance
Online-Zugang:	Volltext
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