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GpGp  

Fast Gaussian Process Computation Using Vecchia's Approximation
View on CRAN: Click here


Download and install GpGp package within the R console
Install from CRAN:
install.packages("GpGp")

Install from Github:
library("remotes")
install_github("cran/GpGp")

Install by package version:
library("remotes")
install_version("GpGp", "1.0.0")



Attach the package and use:
library("GpGp")
Maintained by
Joseph Guinness
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-02-19
Latest Update: 2024-10-16
Description:
Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) , and the reordering and grouping methods are from Guinness (2018) . Model fitting employs a Fisher scoring algorithm described in Guinness (2019) .
How to cite:
Joseph Guinness (2018). GpGp: Fast Gaussian Process Computation Using Vecchia's Approximation. R package version 1.0.0, https://cran.r-project.org/web/packages/GpGp. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1.0 (2018-02-19 11:14), 0.1.1 (2019-01-30 10:20), 0.2.0 (2019-06-29 14:40), 0.2.1 (2019-07-09 16:40), 0.2.2 (2020-07-12 07:30), 0.3.0 (2020-10-03 07:10), 0.3.1 (2020-10-17 06:40), 0.3.2 (2021-01-27 22:30), 0.4.0 (2021-06-09 23:40), 0.5.0 (2024-02-19 00:00), 0.5.1 (2024-10-16 06:30)
Other packages that cited GpGp R package
View GpGp citation profile
Other R packages that GpGp depends, imports, suggests or enhances
Complete documentation for GpGp
Functions, R codes and Examples using the GpGp R package
Some associated functions: GpGp . L_mult . L_t_mult . Linv_mult . Linv_t_mult . argo2016 . cond_sim . condition_number . expit . exponential_anisotropic2D . exponential_anisotropic3D . exponential_anisotropic3D_alt . exponential_isotropic . exponential_nonstat_var . exponential_scaledim . exponential_spacetime . exponential_sphere . exponential_sphere_warp . exponential_spheretime . exponential_spheretime_warp . fast_Gp_sim . fast_Gp_sim_Linv . find_ordered_nn . find_ordered_nn_brute . fisher_scoring . fit_model . get_linkfun . get_penalty . get_start_parms . group_obs . jason3 . matern15_isotropic . matern15_scaledim . matern25_isotropic . matern25_scaledim . matern35_isotropic . matern35_scaledim . matern45_isotropic . matern45_scaledim . matern_anisotropic2D . matern_anisotropic3D . matern_anisotropic3D_alt . matern_categorical . matern_isotropic . matern_nonstat_var . matern_scaledim . matern_spacetime . matern_spacetime_categorical . matern_spacetime_categorical_local . matern_sphere . matern_sphere_warp . matern_spheretime . matern_spheretime_warp . order_coordinate . order_dist_to_point . order_maxmin . order_middleout . pen_hi . pen_lo . pen_loglo . predictions . sph_grad_xyz . summary.GpGp_fit . test_likelihood_object . vecchia_Linv . vecchia_grouped_meanzero_loglik . vecchia_grouped_profbeta_loglik . vecchia_grouped_profbeta_loglik_grad_info . vecchia_meanzero_loglik . vecchia_profbeta_loglik . vecchia_profbeta_loglik_grad_info . 
Some associated R codes: GpGp.R . RcppExports.R . Rcpp_doc.R . argo2016.R . fisher_scoring.R . fit_model.R . jason3.R . nearest_neighbor_functions.R . ordering_functions.R . penalties.R . predictions.R . simulation_functions.R .  Full GpGp package functions and examples
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