Package: RKHSMetaMod 1.1

Halaleh Kamari

RKHSMetaMod: Ridge Group Sparse Optimization Problem for Estimation of a Meta Model Based on Reproducing Kernel Hilbert Spaces

Estimates the Hoeffding decomposition of an unknown function by solving ridge group sparse optimization problem based on reproducing kernel Hilbert spaces, and approximates its sensitivity indices (see Kamari, H., Huet, S. and Taupin, M.-L. (2019) <arxiv:1905.13695>).

Authors:Halaleh Kamari

RKHSMetaMod_1.1.tar.gz
RKHSMetaMod_1.1.tar.gz(r-4.5-noble)RKHSMetaMod_1.1.tar.gz(r-4.4-noble)
RKHSMetaMod_1.1.tgz(r-4.4-emscripten)RKHSMetaMod_1.1.tgz(r-4.3-emscripten)
RKHSMetaMod.pdf |RKHSMetaMod.html✨
RKHSMetaMod/json (API)

# Install 'RKHSMetaMod' in R:

install.packages('RKHSMetaMod', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

gsl– GNU Scientific Library (GSL)
c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

gsl cpp

1.00 score 1 scripts 140 downloads 9 exports 3 dependencies

Last updated 5 years agofrom:ac09bd133e. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 03 2024
R-4.5-linux-x86_64	OK	Dec 03 2024

Exports:calc_Kv grplasso_q mu_max pen_MetMod PredErr RKHSgrplasso RKHSMetMod RKHSMetMod_qmax SI_emp

Dependencies:Rcpp RcppEigen RcppGSL

Citation

Readme and manuals

Help Manual

Help page	Topics
Set of Rcpp and R functions to produce a sequence of meta models that are the solutions of the RKHS Ridge Group Sparse or RKHS Group Lasso optimization problems, calulate their associated prediction errors as well as their empirical sensitivity indices.	RKHSMetaMod-package RKHSMetaMod
Function to calculate the Gram matrices and their eigenvalues and eigenvectors for a chosen reproducing kernel.	calc_Kv
Function to fit a solution with q active groups of an RKHS Group Lasso problem.	grplasso_q
Function to find the maximal value of the penalty parameter in the RKHS Group Lasso problem.	mu_max
Function to fit a solution of the RKHS Ridge Group Sparse problem.	pen_MetMod
Function to calculate the prediction error.	PredErr
Function to fit a solution of an RKHS Group Lasso problem.	RKHSgrplasso
Function to produce a sequence of meta models that are the solutions of the RKHS Ridge Group Sparse or RKHS Group Lasso optimization problems.	RKHSMetMod
Function to produce a sequence of meta models, with at most qmax active groups in each meta model. The meta models are the solutions of the RKHS Ridge Group Sparse or RKHS Group Lasso optimization problems.	RKHSMetMod_qmax
Function to calculate the empirical sensitivity indices for an input or a group of inputs.	SI_emp

Package: RKHSMetaMod 1.1

RKHSMetaMod: Ridge Group Sparse Optimization Problem for Estimation of a Meta Model Based on Reproducing Kernel Hilbert Spaces

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)