Package: SSM 1.0.1

SSM: Fit and Analyze Smooth Supersaturated Models

Creates an S4 class "SSM" and defines functions for fitting smooth supersaturated models, a polynomial model with spline-like behaviour. Functions are defined for the computation of Sobol indices for sensitivity analysis and plotting the main effects using FANOVA methods. It also implements the estimation of the SSM metamodel error using a GP model with a variety of defined correlation functions.

Authors:Peter Curtis [aut, cre]

SSM_1.0.1.tar.gz
SSM_1.0.1.zip(r-4.5)SSM_1.0.1.zip(r-4.4)SSM_1.0.1.zip(r-4.3)
SSM_1.0.1.tgz(r-4.4-any)SSM_1.0.1.tgz(r-4.3-any)
SSM_1.0.1.tar.gz(r-4.5-noble)SSM_1.0.1.tar.gz(r-4.4-noble)
SSM_1.0.1.tgz(r-4.4-emscripten)SSM_1.0.1.tgz(r-4.3-emscripten)
SSM.pdf |SSM.html✨
SSM/json (API)

# Install 'SSM' in R:
install.packages('SSM', repos = c('https://peterrobertcurtis.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/peterrobertcurtis/ssm/issues

On CRAN:

4.70 score 9 scripts 133 downloads 183 mentions 5 exports 0 dependencies

Last updated 7 years agofrom:c8e0b971cf. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winNOTENov 22 2024
R-4.5-linuxNOTENov 22 2024
R-4.4-winNOTENov 22 2024
R-4.4-macNOTENov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:fit.ssmlikelihood.plotsensitivity.plotshowtransform11

Dependencies:

Smooth supersaturated models

Peter Curtis

Rendered fromSSM.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2017-01-18
Started: 2017-01-18