Maximum likelihood estimation of regression parameters with spatially dependent discrete data

DOI10.1198/jabes.2009.07116zbMath1306.62310OpenAlexW2046299501MaRDI QIDQ2260102

L. B. Madsen

Publication date: 5 March 2015

Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/jabes.2009.07116

zbMATH Keywords

continuous extensionGaussian copulaspatial copulacorrelated count datadependent count data

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Related Items (7)

Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data ⋮ Maximum likelihood estimation of Gaussian copula models for geostatistical count data ⋮ On the estimation of normal copula discrete regression models using the continuous extension and simulated likelihood ⋮ Nearest-neighbor mixture models for non-Gaussian spatial processes ⋮ On the occasional exactness of the distributional transform approximation for direct Gaussian copula models with discrete margins ⋮ Joint Regression Analysis for Discrete Longitudinal Data ⋮ Models for Geostatistical Binary Data: Properties and Connections

Uses Software

• Matlab
• R
• MASS (R)

Cites Work

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