SSM: SSM: A package for fitting smooth supersaturated models...
In SSM: Fit and Analyze Smooth Supersaturated Models
Description
The SSM package provides an S4 class to represent smooth supersaturated
models, along with functions for fitting SSM to data, computing Sobol indices
for the SSM and estimating metamodel error with a Gaussian process.
SSM functions
There are three important functions in the package.
fit.ssm returns an SSM object that fits an SSM to the data and, by
default, computes the Sobol indices, and Total interaction indices of the
model. Optionally, the metamodel error can be estimated using a Gaussian
process. The fitted SSM smooths over [-1, 1]^d and uses a hierarchical
basis of 20*d+n Legendre polynomials by default but the function is highly
customisable.
predict.SSM returns the model prediction at a point, including a
credible interval if a metamodel error GP has been fit.
plot.SSM plots the main effects of the SSM.
SSM documentation built on May 1, 2019, 10:09 p.m.
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Description
The SSM package provides an S4 class to represent smooth supersaturated models, along with functions for fitting SSM to data, computing Sobol indices for the SSM and estimating metamodel error with a Gaussian process.
SSM functions
There are three important functions in the package.
fit.ssm returns an SSM object that fits an SSM to the data and, by
default, computes the Sobol indices, and Total interaction indices of the
model. Optionally, the metamodel error can be estimated using a Gaussian
process. The fitted SSM smooths over [-1, 1]^d and uses a hierarchical
basis of 20*d+n Legendre polynomials by default but the function is highly
customisable.
predict.SSM returns the model prediction at a point, including a
credible interval if a metamodel error GP has been fit.
plot.SSM plots the main effects of the SSM.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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