R: Convolution-Based Nonstationary Spatial Modeling

# Convolution-Based Nonstationary Spatial Modeling

## Documentation for package ‘convoSPAT’ version 1.2.7

- DESCRIPTION file

## Help Pages

Aniso_fit | Fit the stationary spatial model
cov_spatial | Calculate spatial covariance.
evaluate_CV | Evaluation criteria
f_mc_kernels | Calculate mixture component kernel matrices.
kernel_cov | Calculate a kernel covariance matrix.
make_global_loglik1 | Constructor functions for global parameter estimation.
make_global_loglik1_kappa | Constructor functions for global parameter estimation.
make_global_loglik2 | Constructor functions for global parameter estimation.
make_global_loglik2_kappa | Constructor functions for global parameter estimation.
make_global_loglik3 | Constructor functions for global parameter estimation.
make_global_loglik3_kappa | Constructor functions for global parameter estimation.
make_global_loglik4_kappa | Constructor functions for global parameter estimation.
make_local_lik | Constructor functions for local parameter estimation.
mc_N | Calculate local sample sizes.
NSconvo_fit | Fit the nonstationary spatial model
NSconvo_sim | Simulate data from the nonstationary model.
plot.Aniso | Plot of the estimated correlations from the stationary model.
plot.NSconvo | Plot from the nonstationary model.
predict.Aniso | Obtain predictions at unobserved locations for the stationary spatial model.
predict.NSconvo | Obtain predictions at unobserved locations for the nonstationary spatial model.
simdata | Simulated nonstationary dataset
summary.Aniso | Summarize the stationary model fit.
summary.NSconvo | Summarize the nonstationary model fit.
US.mc.grids | Mixture component grids for the western United States
US.prediction.locs | Prediction locations for the western United States
USprecip97 | Annual precipitation measurements from the western United States, 1997