R: Gaussian Process Based Design and Analysis for the Active Subspace Method

# Gaussian Process Based Design and Analysis for the Active Subspace Method

## Documentation for package ‘activegp’ version 1.1.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

activegp | Package activegp
as.matrix.const_C | Extract Matrix
C_GP | Active Subspace Matrix closed form expression for a GP.
C_GP_ci | CI on Eigenvalues via Monte Carlo/GP
C_tr | Expected variance of trace of C
C_var | Element-wise Cn+1 variance
C_var2 | Alternative Variance of Update
domain_to_R | Rectangular Domain -> Unbounded Domain
domain_to_unit | Change a function's inputs to live in [-1, 1]
grad_est_subspace | Estimate the Active Subspace of a Cheap Function using Gradients
logLikHessian | Hessian of the log-likelihood with respect to lengthscales hyperparameters Works for homGP and hetGP models from the hetGP package for now.
Lt_GP | Active Subspace Prewarping
n11_2_01 | f:[-1, 1] -> R Becomes f:[0,1] -> R
plot.const_C | Plot const_C objectc
print.const_C | Print const_C objects
subspace_dist | Get the distance between subspaces defined as the ranges of A and B
update.const_C | C update with new observations
update_C2 | Update Constantine's C, using update formula