# Fast Gaussian Process Computation Using Vecchia's Approximation

## Documentation for package ‘GpGp’ version 1.0.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

A C D E F G I J L M O P S T V

GpGp-package | GpGp: Fast Gaussian Process Computing.

## -- A --

argo2016 | Ocean temperatures from Argo profiling floats

## -- C --

condition_number | compute condition number of matrix
cond_sim | Conditional Simulation using Vecchia's approximation

## -- D --

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

## -- E --

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

## -- F --

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

## -- G --

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

## -- I --

intexpit | expit function and integral of expit function

## -- J --

jason3 | Windspeed measurements from Jason-3 Satellite

## -- L --

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

## -- M --

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

## -- O --

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

## -- P --

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

## -- S --

sph_grad_xyz | compute gradient of spherical harmonics functions
summary.GpGp_fit | Print summary of GpGp fit

## -- T --

test_likelihood_object | test likelihood object for NA or Inf values

## -- V --

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