Package index • GauPro

All functions

k_Cubic(): Cubic Kernel R6 class
k_Exponential(): Exponential Kernel R6 class
k_FactorKernel(): Factor Kernel R6 class
GauPro(): GauPro_selector
GauPro_Gauss: Corr Gauss GP using inherited optim
GauPro_Gauss_LOO: Corr Gauss GP using inherited optim
GauPro_base: Class providing object with methods for fitting a GP model
GauPro_kernel: Kernel R6 class
GauPro_kernel_beta: Beta Kernel R6 class
GauPro_kernel_model: Gaussian process model with kernel
GauPro_kernel_model_LOO: Corr Gauss GP using inherited optim
GauPro_trend: Trend R6 class
k_Gaussian(): Gaussian Kernel R6 class
Gaussian_devianceC(): Calculate the Gaussian deviance in C
Gaussian_hessianC(): Calculate Hessian for a GP with Gaussian correlation
Gaussian_hessianCC(): Gaussian hessian in C
Gaussian_hessianR(): Calculate Hessian for a GP with Gaussian correlation
k_GowerFactorKernel(): Gower factor Kernel R6 class
k_IgnoreIndsKernel(): Kernel R6 class
k_LatentFactorKernel(): Latent Factor Kernel R6 class
k_Matern32(): Matern 3/2 Kernel R6 class
k_Matern52(): Matern 5/2 Kernel R6 class
k_OrderedFactorKernel(): Ordered Factor Kernel R6 class
k_Periodic(): Periodic Kernel R6 class
k_PowerExp(): Power Exponential Kernel R6 class
k_RatQuad(): Rational Quadratic Kernel R6 class
k_Triangle(): Triangle Kernel R6 class
k_White(): White noise Kernel R6 class
arma_mult_cube_vec(): Cube multiply over first dimension
corr_cubic_matrix_symC(): Correlation Cubic matrix in C (symmetric)
corr_exponential_matrix_symC(): Correlation Gaussian matrix in C (symmetric)
corr_gauss_dCdX(): Correlation Gaussian matrix gradient in C using Armadillo
corr_gauss_matrix(): Gaussian correlation
corr_gauss_matrixC(): Correlation Gaussian matrix in C using Rcpp
corr_gauss_matrix_armaC(): Correlation Gaussian matrix in C using Armadillo
corr_gauss_matrix_symC(): Correlation Gaussian matrix in C (symmetric)
corr_gauss_matrix_sym_armaC(): Correlation Gaussian matrix in C using Armadillo (symmetric)
corr_latentfactor_matrix_symC(): Correlation Latent factor matrix in C (symmetric)
corr_latentfactor_matrixmatrixC(): Correlation Latent factor matrix in C (symmetric)
corr_matern32_matrix_symC(): Correlation Matern 3/2 matrix in C (symmetric)
corr_matern52_matrix_symC(): Correlation Gaussian matrix in C (symmetric)
corr_orderedfactor_matrix_symC(): Correlation ordered factor matrix in C (symmetric)
corr_orderedfactor_matrixmatrixC(): Correlation ordered factor matrix in C (symmetric)
gpkm(): Gaussian process regression model
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(): Calculate gradfunc in optimization to speed up. NEEDS TO APERM dC_dparams Doesn't need to be exported, should only be useful in functions.
kernel_cubic_dC(): Derivative of cubic kernel covariance matrix in C
kernel_exponential_dC(): Derivative of Matern 5/2 kernel covariance matrix in C
kernel_gauss_dC(): Derivative of Gaussian kernel covariance matrix in C
kernel_latentFactor_dC(): Derivative of covariance matrix of X with respect to kernel parameters for the Latent Factor Kernel
kernel_matern32_dC(): Derivative of Matern 5/2 kernel covariance matrix in C
kernel_matern52_dC(): Derivative of Matern 5/2 kernel covariance matrix in C
kernel_orderedFactor_dC(): Derivative of covariance matrix of X with respect to kernel parameters for the Ordered Factor Kernel
kernel_product: Gaussian Kernel R6 class
kernel_sum: Gaussian Kernel R6 class
`+`(<GauPro_kernel>): Kernel sum
predict(<GauPro>): Predict for class GauPro
predict(<GauPro_base>): Predict for class GauPro_base
print(<summary.GauPro>): Print summary.GauPro
sqrt_matrix(): Find the square root of a matrix
summary(<GauPro>): Summary for GauPro object
`*`(<GauPro_kernel>): Kernel product
trend_0: Trend R6 class
trend_LM: Trend R6 class
trend_c: Trend R6 class