On the Correlation Structure of Gaussian Copula Models for Geostatistical Count Data

DOI10.1111/anzs.12140zbMath1373.62560OpenAlexW2335838176MaRDI QIDQ5361191

Zifei Han, Victor De Oliveira

Publication date: 27 September 2017

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/anzs.12140

zbMATH Keywords

isotropyGaussian random fieldnegative binomialPoisson-gamma modelFréchet-Hoeffding upper boundzero-inflated Poissongeostatistical count data

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Applications of statistics to environmental and related topics (62P12) Measures of association (correlation, canonical correlation, etc.) (62H20) Geostatistics (86A32)

Related Items (9)

Maximum likelihood estimation of Gaussian copula models for geostatistical count data ⋮ Count Time Series: A Methodological Review ⋮ Analyzing longitudinal clustered count data with zero inflation: Marginal modeling using the Conway–Maxwell–Poisson distribution ⋮ Latent Gaussian Count Time Series ⋮ Seasonal count time series ⋮ On the occasional exactness of the distributional transform approximation for direct Gaussian copula models with discrete margins ⋮ Sklar's Omega: A Gaussian Copula-Based Framework for Assessing Agreement ⋮ Modelling Point Referenced Spatial Count Data: A Poisson Process Approach ⋮ Models for Geostatistical Binary Data: Properties and Connections

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