Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Zifei Han, Victor De Oliveira
Title: gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas
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.

Page views:: 5900. Submitted: 2017-04-18. Published: 2018-12-21.
Paper: gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas     Download PDF (Downloads: 1011)
gcKrig_1.1.3.tar.gz: R source package Download (Downloads: 86; 88KB)
v87i13.R: R replication code Download (Downloads: 129; 14KB)

DOI: 10.18637/jss.v087.i13

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.