GpGp-package | GpGp: Fast Gaussian Process Computing. |
argo2016 | Ocean temperatures from Argo profiling floats |
condition_number | compute condition number of matrix |
cond_sim | Conditional Simulation using Vecchia's approximation |
ddpen_hi | penalize large values of parameter: penalty, 1st deriative, 2nd derivative |
ddpen_lo | penalize small values of parameter: penalty, 1st deriative, 2nd derivative |
ddpen_loglo | penalize small values of log parameter: penalty, 1st deriative, 2nd derivative |
dpen_hi | penalize large values of parameter: penalty, 1st deriative, 2nd derivative |
dpen_lo | penalize small values of parameter: penalty, 1st deriative, 2nd derivative |
dpen_loglo | penalize small values of log parameter: penalty, 1st deriative, 2nd derivative |
d_exponential_anisotropic2D | Geometrically anisotropic exponential covariance function (two dimensions) |
d_exponential_anisotropic3D | Geometrically anisotropic exponential covariance function (three dimensions) |
d_exponential_anisotropic3D_alt | Geometrically anisotropic exponential covariance function (three dimensions, alternate parameterization) |
d_exponential_isotropic | Isotropic exponential covariance function |
d_exponential_nonstat_var | Isotropic exponential covariance function, nonstationary variances |
d_exponential_scaledim | Exponential covariance function, different range parameter for each dimension |
d_exponential_spacetime | Spatial-Temporal exponential covariance function |
d_exponential_sphere | Isotropic exponential covariance function on sphere |
d_exponential_spheretime | Exponential covariance function on sphere x time |
d_exponential_spheretime_warp | Deformed exponential covariance function on sphere |
d_exponential_sphere_warp | Deformed exponential covariance function on sphere |
d_matern15_isotropic | Isotropic exponential covariance function |
d_matern15_scaledim | Matern covariance function, smoothess = 1.5, different range parameter for each dimension |
d_matern25_isotropic | Isotropic exponential covariance function |
d_matern25_scaledim | Matern covariance function, smoothess = 2.5, different range parameter for each dimension |
d_matern35_isotropic | Isotropic Matern covariance function, smoothness = 3.5 |
d_matern35_scaledim | Matern covariance function, smoothess = 3.5, different range parameter for each dimension |
d_matern45_isotropic | Isotropic Matern covariance function, smoothness = 3.5 |
d_matern45_scaledim | Matern covariance function, smoothess = 3.5, different range parameter for each dimension |
d_matern_anisotropic2D | Geometrically anisotropic Matern covariance function (two dimensions) |
d_matern_anisotropic3D | Geometrically anisotropic Matern covariance function (three dimensions) |
d_matern_anisotropic3D_alt | Geometrically anisotropic Matern covariance function (three dimensions) |
d_matern_categorical | Isotropic Matern covariance function with random effects for categories |
d_matern_isotropic | Isotropic Matern covariance function |
d_matern_nonstat_var | Isotropic Matern covariance function, nonstationary variances |
d_matern_scaledim | Matern covariance function, different range parameter for each dimension |
d_matern_spacetime | Spatial-Temporal Matern covariance function |
d_matern_spacetime_categorical | Space-Time Matern covariance function with random effects for categories |
d_matern_spacetime_categorical_local | Space-Time Matern covariance function with local random effects for categories |
d_matern_sphere | Isotropic Matern covariance function on sphere |
d_matern_spheretime | Matern covariance function on sphere x time |
d_matern_spheretime_warp | Deformed Matern covariance function on sphere |
d_matern_sphere_warp | Deformed Matern covariance function on sphere |
expit | expit function and integral of expit function |
exponential_anisotropic2D | Geometrically anisotropic exponential covariance function (two dimensions) |
exponential_anisotropic3D | Geometrically anisotropic exponential covariance function (three dimensions) |
exponential_anisotropic3D_alt | Geometrically anisotropic exponential covariance function (three dimensions, alternate parameterization) |
exponential_isotropic | Isotropic exponential covariance function |
exponential_nonstat_var | Isotropic exponential covariance function, nonstationary variances |
exponential_scaledim | Exponential covariance function, different range parameter for each dimension |
exponential_spacetime | Spatial-Temporal exponential covariance function |
exponential_sphere | Isotropic exponential covariance function on sphere |
exponential_spheretime | Exponential covariance function on sphere x time |
exponential_spheretime_warp | Deformed exponential covariance function on sphere |
exponential_sphere_warp | Deformed exponential covariance function on sphere |
fast_Gp_sim | Approximate GP simulation |
fast_Gp_sim_Linv | Approximate GP simulation with specified Linverse |
find_ordered_nn | Find ordered nearest neighbors. |
find_ordered_nn_brute | Naive brute force nearest neighbor finder |
fisher_scoring | Fisher scoring algorithm |
fit_model | Estimate mean and covariance parameters |
get_linkfun | get link function, whether locations are lonlat and space time |
get_penalty | get penalty function |
get_start_parms | get default starting values of covariance parameters |
GpGp | GpGp: Fast Gaussian Process Computing. |
group_obs | Automatic grouping (partitioning) of locations |
intexpit | expit function and integral of expit function |
jason3 | Windspeed measurements from Jason-3 Satellite |
Linv_mult | Multiply approximate inverse Cholesky by a vector |
Linv_t_mult | Multiply transpose of approximate inverse Cholesky by a vector |
L_mult | Multiply approximate Cholesky by a vector |
L_t_mult | Multiply transpose of approximate Cholesky by a vector |
matern15_isotropic | Isotropic Matern covariance function, smoothness = 1.5 |
matern15_scaledim | Matern covariance function, smoothess = 1.5, different range parameter for each dimension |
matern25_isotropic | Isotropic Matern covariance function, smoothness = 2.5 |
matern25_scaledim | Matern covariance function, smoothess = 2.5, different range parameter for each dimension |
matern35_isotropic | Isotropic Matern covariance function, smoothness = 3.5 |
matern35_scaledim | Matern covariance function, smoothess = 3.5, different range parameter for each dimension |
matern45_isotropic | Isotropic Matern covariance function, smoothness = 4.5 |
matern45_scaledim | Matern covariance function, smoothess = 3.5, different range parameter for each dimension |
matern_anisotropic2D | Geometrically anisotropic Matern covariance function (two dimensions) |
matern_anisotropic3D | Geometrically anisotropic Matern covariance function (three dimensions) |
matern_anisotropic3D_alt | Geometrically anisotropic Matern covariance function (three dimensions, alternate parameterization) |
matern_categorical | Isotropic Matern covariance function with random effects for categories |
matern_isotropic | Isotropic Matern covariance function |
matern_nonstat_var | Isotropic Matern covariance function, nonstationary variances |
matern_scaledim | Matern covariance function, different range parameter for each dimension |
matern_spacetime | Spatial-Temporal Matern covariance function |
matern_spacetime_categorical | Space-Time Matern covariance function with random effects for categories |
matern_spacetime_categorical_local | Space-Time Matern covariance function with local random effects for categories |
matern_sphere | Isotropic Matern covariance function on sphere |
matern_spheretime | Matern covariance function on sphere x time |
matern_spheretime_warp | Deformed Matern covariance function on sphere |
matern_sphere_warp | Deformed Matern covariance function on sphere |
order_coordinate | Sorted coordinate ordering |
order_dist_to_point | Distance to specified point ordering |
order_maxmin | Maximum minimum distance ordering |
order_middleout | Middle-out ordering |
pen_hi | penalize large values of parameter: penalty, 1st deriative, 2nd derivative |
pen_lo | penalize small values of parameter: penalty, 1st deriative, 2nd derivative |
pen_loglo | penalize small values of log parameter: penalty, 1st deriative, 2nd derivative |
predictions | Compute Gaussian process predictions using Vecchia's approximations |
sph_grad_xyz | compute gradient of spherical harmonics functions |
summary.GpGp_fit | Print summary of GpGp fit |
test_likelihood_object | test likelihood object for NA or Inf values |
vecchia_grouped_meanzero_loglik | Grouped Vecchia approximation to the Gaussian loglikelihood, zero mean |
vecchia_grouped_profbeta_loglik | Grouped Vecchia approximation, profiled regression coefficients |
vecchia_grouped_profbeta_loglik_grad_info | Grouped Vecchia loglikelihood, gradient, Fisher information |
vecchia_Linv | Entries of inverse Cholesky approximation |
vecchia_meanzero_loglik | Vecchia's approximation to the Gaussian loglikelihood, zero mean |
vecchia_profbeta_loglik | Vecchia's approximation to the Gaussian loglikelihood, with profiled regression coefficients. |
vecchia_profbeta_loglik_grad_info | Vecchia's loglikelihood, gradient, and Fisher information |