Package: GauPro 0.2.17.9000

GauPro: Gaussian Process Fitting

Fits a Gaussian process model to data. Gaussian processes are commonly used in computer experiments to fit an interpolating model. The model is stored as an 'R6' object and can be easily updated with new data. There are options to run in parallel, and 'Rcpp' has been used to speed up calculations. For more info about Gaussian process software, see Erickson et al. (2018) <doi:10.1016/j.ejor.2017.10.002>.

Authors:Collin Erickson [aut, cre]

GauPro_0.2.17.9000.tar.gz
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GauPro_0.2.17.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GauPro/json (API)
NEWS

# Install 'GauPro' in R:
install.packages('GauPro', repos = c('https://collinerickson.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/collinerickson/gaupro/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

openblascppopenmp

11.41 score 19 stars 51 packages 116 scripts 38k downloads 1 mentions 71 exports 56 dependencies

Last updated from:02fb70f74a. Checks:12 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK305
linux-devel-x86_64OK358
source / vignettesOK428
linux-release-arm64OK303
linux-release-x86_64OK333
macos-release-arm64OK254
macos-release-x86_64OK464
macos-oldrel-arm64OK172
macos-oldrel-x86_64OK450
windows-develOK353
windows-releaseOK352
windows-oldrelERROR352
wasm-releaseOK204

Exports:arma_mult_cube_veccorr_cubic_matrix_symCcorr_exponential_matrix_symCcorr_gauss_dCdXcorr_gauss_matrixcorr_gauss_matrix_armaCcorr_gauss_matrix_sym_armaCcorr_gauss_matrix_symCcorr_gauss_matrixCcorr_latentfactor_matrix_symCcorr_latentfactor_matrixmatrixCcorr_matern32_matrix_symCcorr_matern52_matrix_symCcorr_orderedfactor_matrix_symCcorr_orderedfactor_matrixmatrixCCubicExponentialFactorKernelGauProGauPro_baseGauPro_GaussGauPro_Gauss_LOOGauPro_kernel_modelGauPro_kernel_model_LOOGaussianGaussian_devianceCGaussian_hessianCGaussian_hessianCCGaussian_hessianRGowerFactorKernelgpkmgradfuncarraygradfuncarrayRIgnoreIndsKernelk_Cubick_Exponentialk_FactorKernelk_Gaussiank_GowerFactorKernelk_IgnoreIndsKernelk_LatentFactorKernelk_Matern32k_Matern52k_OrderedFactorKernelk_Periodick_PowerExpk_RatQuadk_Trianglek_Whitekernel_cubic_dCkernel_exponential_dCkernel_gauss_dCkernel_latentFactor_dCkernel_matern32_dCkernel_matern52_dCkernel_orderedFactor_dCkernel_productkernel_sumLatentFactorKernelMatern32Matern52OrderedFactorKernelPeriodicPowerExpRatQuadsqrt_matrixtrend_0trend_ctrend_LMTriangleWhite

Dependencies:base64encbslibcachemclicpp11digestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolsisobandjquerylibjsonliteknitrlabelinglbfgslifecyclemagrittrmemoisemimemixoptnumDerivpillarpkgconfigpurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownS7sassscalessplitfngrstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

A Guide to the GauPro R package

Collin Erickson

Rendered fromGauPro.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2025-03-09
Started: 2017-03-26

Derivatives for estimating Gaussian process parameters

Collin Erickson

Rendered fromderivatives.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2024-09-24
Started: 2016-10-20

Introduction to Gaussian Processes

Collin Erickson

Rendered fromIntroductionToGPs.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2024-09-29
Started: 2017-05-27

Leave-one-out cross-validation and error correction

Collin Erickson

Rendered fromCrossValidationErrorCorrection.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2017-09-15
Started: 2017-06-05

Spatial derivatives of Gaussian process models

Collin Erickson

Rendered fromsurface_derivatives.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2024-10-23
Started: 2016-11-17

Readme and manuals

Help Manual

Help pageTopics
Kernel product*.GauPro_kernel
Kernel sum+.GauPro_kernel
Cube multiply over first dimensionarma_mult_cube_vec
Correlation Cubic matrix in C (symmetric)corr_cubic_matrix_symC
Correlation Gaussian matrix in C (symmetric)corr_exponential_matrix_symC
Correlation Gaussian matrix gradient in C using Armadillocorr_gauss_dCdX
Gaussian correlationcorr_gauss_matrix
Correlation Gaussian matrix in C using Armadillocorr_gauss_matrix_armaC
Correlation Gaussian matrix in C using Armadillo (symmetric)corr_gauss_matrix_sym_armaC
Correlation Gaussian matrix in C (symmetric)corr_gauss_matrix_symC
Correlation Gaussian matrix in C using Rcppcorr_gauss_matrixC
Correlation Latent factor matrix in C (symmetric)corr_latentfactor_matrix_symC
Correlation Latent factor matrix in C (symmetric)corr_latentfactor_matrixmatrixC
Correlation Matern 3/2 matrix in C (symmetric)corr_matern32_matrix_symC
Correlation Gaussian matrix in C (symmetric)corr_matern52_matrix_symC
Correlation ordered factor matrix in C (symmetric)corr_orderedfactor_matrix_symC
Correlation ordered factor matrix in C (symmetric)corr_orderedfactor_matrixmatrixC
Cubic Kernel R6 classCubic k_Cubic
Exponential Kernel R6 classExponential k_Exponential
Factor Kernel R6 classFactorKernel k_FactorKernel
GauPro_selectorGauPro
Class providing object with methods for fitting a GP modelGauPro_base
Corr Gauss GP using inherited optimGauPro_Gauss
Corr Gauss GP using inherited optimGauPro_Gauss_LOO
Kernel R6 classGauPro_kernel
Beta Kernel R6 classGauPro_kernel_beta
Gaussian process model with kernelGauPro_kernel_model
Corr Gauss GP using inherited optimGauPro_kernel_model_LOO
Trend R6 classGauPro_trend
Gaussian Kernel R6 classGaussian k_Gaussian
Calculate the Gaussian deviance in CGaussian_devianceC
Calculate Hessian for a GP with Gaussian correlationGaussian_hessianC
Gaussian hessian in CGaussian_hessianCC
Calculate Hessian for a GP with Gaussian correlationGaussian_hessianR
Gower factor Kernel R6 classGowerFactorKernel k_GowerFactorKernel
Gaussian process regression modelgpkm
Calculate gradfunc in optimization to speed up. NEEDS TO APERM dC_dparams Doesn't need to be exported, should only be useful in functions.gradfuncarray
Calculate gradfunc in optimization to speed up. NEEDS TO APERM dC_dparams Doesn't need to be exported, should only be useful in functions.gradfuncarrayR
Kernel R6 classIgnoreIndsKernel k_IgnoreIndsKernel
Derivative of cubic kernel covariance matrix in Ckernel_cubic_dC
Derivative of Matern 5/2 kernel covariance matrix in Ckernel_exponential_dC
Derivative of Gaussian kernel covariance matrix in Ckernel_gauss_dC
Derivative of covariance matrix of X with respect to kernel parameters for the Latent Factor Kernelkernel_latentFactor_dC
Derivative of Matern 5/2 kernel covariance matrix in Ckernel_matern32_dC
Derivative of Matern 5/2 kernel covariance matrix in Ckernel_matern52_dC
Derivative of covariance matrix of X with respect to kernel parameters for the Ordered Factor Kernelkernel_orderedFactor_dC
Gaussian Kernel R6 classkernel_product
Gaussian Kernel R6 classkernel_sum
Latent Factor Kernel R6 classk_LatentFactorKernel LatentFactorKernel
Matern 3/2 Kernel R6 classk_Matern32 Matern32
Matern 5/2 Kernel R6 classk_Matern52 Matern52
Ordered Factor Kernel R6 classk_OrderedFactorKernel OrderedFactorKernel
Periodic Kernel R6 classk_Periodic Periodic
Power Exponential Kernel R6 classk_PowerExp PowerExp
Predict for class GauPropredict.GauPro
Predict for class GauPro_basepredict.GauPro_base
Print summary.GauProprint.summary.GauPro
Rational Quadratic Kernel R6 classk_RatQuad RatQuad
Find the square root of a matrixsqrt_matrix
Summary for GauPro objectsummary.GauPro
Trend R6 classtrend_0
Trend R6 classtrend_c
Trend R6 classtrend_LM
Triangle Kernel R6 classk_Triangle Triangle
White noise Kernel R6 classk_White White