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SSM
View on CRAN: Click
here
Download and install SSM package within the R console
Install from CRAN:
install.packages("SSM")
Install from Github:
library("remotes")
install_github("cran/SSM")
Install by package version:
library("remotes")
install_version("SSM", "1.0.1")
Attach the package and use:
library("SSM")
Maintained by
Peter Curtis
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-04
Latest Update: 2017-07-04
Description:
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.
How to cite:
Peter Curtis (2017). SSM: Fit and Analyze Smooth Supersaturated Models. R package version 1.0.1, https://cran.r-project.org/web/packages/SSM
Previous versions and publish date:
No previous versions
Other packages that cited SSM R package
View SSM citation profile
Other R packages that SSM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the SSM R package
Some associated functions: SSM-class . SSM . comb . compute.covariance.from.distance . compute.covariance . compute.interactions . compute.main.effects . compute.residuals . compute.specific.interaction . compute.specific.total.interaction . compute.total.effects . concentrated.likelihood . construct.K.1d . construct.K . construct.P.1d . construct.P . construct.dmm . degl . estimate.GP . find.theta . fit.ssm . get.K.element . identify.main.effect.terms . identify.total.effect.terms . likelihood.plot . lineij . new.distance . optimize.by.interval.maximum . partial.deriv.ssm . plot.SSM . predict.SSM . sensitivity.plot . show-SSM-method . smoothness.over.design . transform11 . update.sensitivity .
Some associated R codes: GP_SSM.R . SSM_class.R . SSM_method.R . fit_SSM.R . plot_SSM.R . sensitivity_SSM.R . Full SSM package functions and examples
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