gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas

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2018
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Abstract
This work describes the R package gcKrig for the analysis of geostatistical count data using Gaussian copulas. The package performs likelihood-based inference and spatial prediction using Gaussian copula models with discrete marginals. Two different classes of methods are implemented to evaluate/approximate the likelihood and the predictive distribution. The package implements the computationally intensive tasks in C++ using an R/C++ interface, and has parallel computing capabilities to predict the response at multiple locations simultaneously. In addition, gcKrig also provides functions to simulate and visualize geostatistical count data, and to compute the correlation function of the counts. It is designed to allow a flexible specification of both the marginals and the spatial correlation function. The principal features of the package are illustrated by three data examples from ecology, agronomy and petrology, and a comparison between gcKrig and two other R packages.
Reference Key
han2018gckrigjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Han, Zifei;Oliveira, Victor De;
Journal journal of statistical software
Year 2018
DOI
DOI not found
URL
https://www.jstatsoft.org/index.php/jss/article/view/3096
Keywords
statistics Agriculture (General) Mineralogy environmental sciences neurology. diseases of the nervous system agriculture forestry electronic computers. computer science

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