corr.gc: Spatial Correlation Functions for Simulation, Likelihood...

In gcKrig: Analysis of Geostatistical Count Data using Gaussian Copulas

Spatial Correlation Functions for Simulation, Likelihood Inference and Spatial Prediction in Gaussian Copula Models with Geostatistical Count Data

Description

Class of isotropic correlation functions available in the gcKrig library.

Details

By default, range parameter is not provided, so this function is used for likelihood inference and spatial prediction with function mlegc and predgc. Users need to specify if the correlation model includes a nugget effect nugget = TRUE or not nugget = FALSE. For Matern and powered exponential correlation functions, the shape parameter kappa is also required from users.

When both range and nugget parameters are given, the function is used to specify the correlation structure in simulation with function simgc in package gcKrig.

Value

At the moment, the following three correlation functins are implemented:

matern.gc	the Matern correlation function.
powerexp.gc	the powered exponential correlation function.
spherical.gc	the spherical correlation function.

Author(s)

Zifei Han [e-mail]

References

De Oliveira, V. (2013) Hierarchical Poisson models for spatial count data. Journal of Multivariate Analysis,122:393-408.

Han, Z. and De Oliveira, V. (2018) gcKrig: An R Package for the Analysis of Geostatistical Count Data Using Gaussian Copulas. Journal of Statistical Software, 87(13), 1–32. doi: 10.18637/jss.v087.i13.

See Also

matern.gc, powerexp.gc, spherical.gc

gcKrig documentation built on July 3, 2022, 1:05 a.m.