Package: activegp 1.1.1
Nathan Wycoff
activegp: Gaussian Process Based Design and Analysis for the Active Subspace Method
The active subspace method is a sensitivity analysis technique that finds important linear combinations of input variables for a simulator. This package provides functions allowing estimation of the active subspace without gradient information using Gaussian processes as well as sequential experimental design tools to minimize the amount of data required to do so. Implements Wycoff et al. (JCGS, 2021) <doi:10.48550/arXiv.1907.11572>.
Authors:
activegp_1.1.1.tar.gz
activegp_1.1.1.tar.gz(r-4.5-noble)activegp_1.1.1.tar.gz(r-4.4-noble)
activegp_1.1.1.tgz(r-4.4-emscripten)activegp_1.1.1.tgz(r-4.3-emscripten)
activegp.pdf |activegp.html✨
activegp/json (API)
NEWS
| # Install 'activegp' in R: |
| install.packages('activegp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:df008c45f4. Checks:1 OK, 1 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 20 2025 |
| R-4.5-linux-x86_64 | NOTE | Feb 20 2025 |
Exports:C_GPC_GP_ciC_GP_cppC_QC_trC_varC_var2domain_to_Rdomain_to_unitgrad_est_subspacelogLikHessianLt_GPn11_2_01quick_Csubspace_distupdate_C2W_kappa_ijW_kappa_ij_upW_kappa_lk
Dependencies:DiceDesignhetGPlhsMASSnumDerivRcppRcppArmadilloRcppProgress
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Package activegp | activegp |
| Extract Matrix | as.matrix.const_C |
| Active Subspace Matrix closed form expression for a GP. | C_GP |
| CI on Eigenvalues via Monte Carlo/GP | C_GP_ci |
| Expected variance of trace of C | C_tr |
| Element-wise Cn+1 variance | C_var |
| Alternative Variance of Update | C_var2 |
| Rectangular Domain -> Unbounded Domain | domain_to_R |
| Change a function's inputs to live in [-1, 1] | domain_to_unit |
| Estimate the Active Subspace of a Cheap Function using Gradients | grad_est_subspace |
| Hessian of the log-likelihood with respect to lengthscales hyperparameters Works for homGP and hetGP models from the hetGP package for now. | logLikHessian |
| Active Subspace Prewarping | Lt_GP |
| f:[-1, 1] -> R Becomes f:[0,1] -> R | n11_2_01 |
| Plot const_C objectc | plot.const_C |
| Print const_C objects | print.const_C |
| Get the distance between subspaces defined as the ranges of A and B | subspace_dist |
| Update Constantine's C, using update formula | update_C2 |
| C update with new observations | update.const_C |