# Gaussian Process Fitting

## Documentation for package ‘GauPro’ version 0.2.11

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

*.GauPro_kernel | Kernel product
+.GauPro_kernel | Kernel sum
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_matrixmatrixC | Correlation Latent factor matrix in C (symmetric)
corr_latentfactor_matrix_symC | 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_matrixmatrixC | Correlation ordered factor matrix in C (symmetric)
corr_orderedfactor_matrix_symC | Correlation ordered factor matrix in C (symmetric)
Cubic | Cubic Kernel R6 class
Exponential | Exponential Kernel R6 class
FactorKernel | Factor Kernel R6 class
GauPro | GauPro_selector
GauPro_base | Class providing object with methods for fitting a GP model
GauPro_Gauss | Corr Gauss GP using inherited optim
GauPro_Gauss_LOO | Corr Gauss GP using inherited optim
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
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
GowerFactorKernel | Gower factor Kernel R6 class
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.
IgnoreIndsKernel | Kernel R6 class
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
LatentFactorKernel | Latent Factor Kernel R6 class
Matern32 | Matern 3/2 Kernel R6 class
Matern52 | Matern 5/2 Kernel R6 class
OrderedFactorKernel | Ordered Factor Kernel R6 class
Periodic | Periodic Kernel R6 class
PowerExp | Power Exponential Kernel R6 class
predict.GauPro | Predict for class GauPro
print.summary.GauPro | Print summary.GauPro
RatQuad | Rational Quadratic Kernel R6 class
sqrt_matrix | Find the square root of a matrix
summary.GauPro | if (F) # Plot is automatically dispatched, same with print and format #' Plot for class GauPro #' #' @param x Object of class GauPro #' @param ... Additional parameters #' #' @return Nothing #' @export #' #' @examples #' n <- 12 #' x <- matrix(seq(0,1,length.out = n), ncol=1) #' y <- sin(2*pi*x) + rnorm(n,0,1e-1) #' gp <- GauPro(X=x, Z=y, parallel=FALSE) #' if (requireNamespace("MASS", quietly = TRUE)) #' plot(gp) #' #' plot.GauPro <- function(x, ...) x$plot(...) # if (x$D == 1) # x$cool1Dplot(...) # else if (x$D == 2) # x$plot2D(...) # else # # stop("No plot method for higher than 2 dimension") # x$plotmarginal() # Summary for GauPro object
trend_0 | Trend R6 class
trend_c | Trend R6 class
trend_LM | Trend R6 class
Triangle | Triangle Kernel R6 class
White | White noise Kernel R6 class