Analysis of binary spatial data by quasi-likelihood estimating equations

DOI10.1214/009053605000000057zbMath1068.62067arXivmath/0505602OpenAlexW3102188253MaRDI QIDQ2388347

Murray K. Clayton, Pei-Sheng Lin

Publication date: 12 September 2005

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0505602

zbMATH Keywords

quasi-likelihood function

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Estimation in multivariate analysis (62H12)

Related Items (16)

An unbalanced multidimensional latent effects-based logistic mixed model and GQL estimation for spatial binary data ⋮ Spatial Confounding in Generalized Estimating Equations ⋮ A comparison of efficiencies between quasi-likelihood and pseudo-likelihood estimates in non-separable spatial-temporal binary data ⋮ Generalized Scan Statistics for Disease Surveillance ⋮ A spatial logistic regression model based on a valid skew-Gaussian latent field ⋮ A generalization of the spatial binary model to the longitudinal spatial setup ⋮ Asymptotic inferences in a multinomial logit mixed model for spatial categorical data ⋮ Fuzzy clusterwise quasi-likelihood generalized linear models ⋮ A generalized bivariate Bernoulli model with covariate dependence ⋮ Block-band behavior of spatial correlations: an analytical asymptotic study in a spatial exponential family data setup ⋮ Efficiency of quasi-likelihood estimation for spatially correlated binary data on \(L_p\) spaces ⋮ Maximum likelihood estimation of regression parameters with spatially dependent discrete data ⋮ A working estimating equation for spatial count data ⋮ Bayesian Analysis of Crossclassified Spatial Data with Autocorrelation ⋮ The Latent Scale Covariogram: A Tool for Exploring the Spatial Dependence Structure of Nonnormal Responses ⋮ Models for Geostatistical Binary Data: Properties and Connections

Cites Work

• Longitudinal data analysis using generalized linear models
• On the central limit theorem for stationary mixing random fields
• Quasi-likelihood functions
• Gaussian and non-Gaussian linear time series and random fields
• A regression model for time series of counts
• Weighted Empirical Adaptive Variance Estimators for Correlated Data Regression
• A Latent Process Regression Model for Spatially Correlated Count Data
• Latent Variable Analysis of Multivariate Spatial Data
• Window Subsampling of Estimating Functions with Application to Regression Models
• A Generalized Estimating Equations Approach for Spatially Correlated Binary Data: Applications to the Analysis of Neuroimaging Data
• Contributions to Central Limit Theory for Dependent Variables
• An Optimum Property of Regular Maximum Likelihood Estimation
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