Bayesian Inference of Spatially Correlated Binary Data Using Skew-Normal Latent Variables with Application in Tooth Caries Analysis

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ISSN Print: 2161-718X
ISSN Online: 2161-7198
www.scirp.org/journal/ojs
E-mail: ojs@scirp.org

"Bayesian Inference of Spatially Correlated Binary Data Using Skew-Normal Latent Variables with Application in Tooth Caries Analysis"
written by Solaiman Afroughi,
published by Open Journal of Statistics, Vol.5 No.2, 2015

has been cited by the following article(s):

[1]	A Spatial Logistic Regression Model Based on a Valid Skew-Gaussian Latent Field
	Journal of Agricultural, Biological and …, 2022

[2]	Flexible Bayesian hierarchical spatial modelling in disease mapping.
	2022

[3]	Tooth Caries Experiences Analysis Among Children Using Centered AutoLogistic Regression Model
	2020

[1]	Multivariate skew-normal distribution for modelling skewed spatial data Spatial and Spatio-temporal Epidemiology, 2024 DOI:10.1016/j.sste.2024.100692

[2]	A Spatial Logistic Regression Model Based on a Valid Skew-Gaussian Latent Field Journal of Agricultural, Biological and Environmental Statistics, 2023 DOI:10.1007/s13253-022-00512-3

[3]	A Spatial Logistic Regression Model Based on a Valid Skew-Gaussian Latent Field Journal of Agricultural, Biological and Environmental Statistics, 2022 DOI:10.1007/s13253-022-00512-3

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