Convolution-Based Nonstationary Spatial Modeling

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Documentation for package ‘convoSPAT’ version 1.2.7

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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