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Description

Bayesian Adaptive Spline Surfaces.

Bayesian fitting and sensitivity analysis methods for adaptive spline surfaces described in <doi:10.18637/jss.v094.i08>. Built to handle continuous and categorical inputs as well as functional or scalar output. An extension of the methodology in Denison, Mallick and Smith (1998) <doi:10.1023/A:1008824606259>.

BASS

License: GPLv3

BASS is an R package for fitting Bayesian Adaptive Spline Surface models available on CRAN with a development version available on GitHub. BASS models most closely resemble Bayesian multivariate adaptive regression splines (Bayesian MARS).

To install the development version, use

# install.packages("devtools")
devtools::install_github("lanl/BASS")

Examples of uses are in Francom et al. (2018) and Francom et al. (2019) and explicit code examples are given in the R package vignette.

References

Francom, Devin, Bruno Sansó, Vera Bulaevskaya, Donald Lucas, and Matthew Simpson. 2019. “Inferring Atmospheric Release Characteristics in a Large Computer Experiment Using Bayesian Adaptive Splines.” Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2018.1562933.

Francom, Devin, Bruno Sansó, Ana Kupresanin, and Gardar Johannesson. 2018. “Sensitivity analysis and emulation for functional data using Bayesian adaptive splines.” Statistica Sinica. https://doi.org/10.5705/ss.202016.0130.

Metadata

Version

1.3.1

License

Unknown

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