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 |