Analysis of Geostatistical Count Data using Gaussian Copulas
The Beta Marginal of Class marginal.gc
The Binomial Marginal of Class marginal.gc
Spatial Correlation Functions for Simulation, Likelihood Inference and...
Compute the Correlation in Transformed Gaussian Random Fields
Compute the Frechet Hoeffding Upper Bound for Given Discrete Marginal ...
The Gamma Marginal of Class marginal.gc
The Gaussian Marginal of Class marginal.gc
Marginals for Data Simulation, Correlation Assessment, Likelihood Infe...
The Matern Correlation Function of Class corr.gc
Maximum Likelihood Estimation in Gaussian Copula Models for Geostatist...
Computing Multivariate Normal Rectangle Probability
The Negative Binomial Marginal of Class marginal.gc
Plot Geostatistical Count Data
Plot Geostatistical Data and Fitted Mean
Plot Geostatistical Data at Sampling and Prediction Locations
Plot Geostatistical Data Simulated From Gaussian Copula
The Poisson Marginal of Class marginal.gc
The Powered Exponential Correlation Function of Class corr.gc
Prediction at Unobserved Locations in Gaussian Copula Models for Geost...
Profile Likelihood Based Confidence Interval of Parameters for Gaussia...
Simulate Geostatistical Data from Gaussian Copula Model at Given Locat...
The Spherical Correlation Function of Class corr.gc
Methods for Extracting Information from Fitted Object of Class `predgc...
Methods for Extracting Information from Fitted Object of Class mlegc
Covariance Matrix of the Maximum Likelihood Estimates
The Weibull Marginal of Class marginal.gc
The Zero-inflated Poisson Marginal of Class marginal.gc
Provides a variety of functions to analyze and model geostatistical count data with Gaussian copulas, including 1) data simulation and visualization; 2) correlation structure assessment (here also known as the Normal To Anything); 3) calculate multivariate normal rectangle probabilities; 4) likelihood inference and parallel prediction at predictive locations. Description of the method is available from: Han and DeOliveira (2018) <doi:10.18637/jss.v087.i13>.