Title: Nonparametric Failure Time Bayesian Additive Regression Trees
Description: Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + s(x) E where functions f and s have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a technical description of the model <https://www.mcw.edu/-/media/MCW/Departments/Biostatistics/tr72.pdf?la=en>.

Description: Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions f and sd have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a technical description of the model <https://www.mcw.edu/-/media/MCW/Departments/Biostatistics/tr72.pdf?la=en>.

Description: This package implements the earthquake ground motion
prediction equations developed as part of the Next Generation
Attenuation of Ground Motions (NGA) project coordinated by the
Pacific Earthquake Engineering Research Center (PEER) in 2008.
Title: NGA Ground Motion Prediction Equations
Author: James Kaklamanos <james.kaklamanos@tufts.edu> and Eric M.

Package: nga
Description: This package implements the earthquake ground motion
prediction equations developed as part of the Next Generation
Attenuation of Ground Motions (NGA) project coordinated by the
Pacific Earthquake Engineering Research Center (PEER) in 2008.
The models implemented in this package are AS08 (Abrahamson &
Silva, 2008), BA08 (Boore & Atkinson, 2008), CB08 (Campbell &
Bozorgnia, 2008), and CY08 (Chiou & Youngs, 2008).  This
numerical implementation has been validated by comparing the
results for 128,000 test cases against the results obtained
using the Fortran implementation composed by David M. Boore and
Kenneth W. Campbell.
Title: NGA Earthquake Ground Motion Prediction Equations
Version: 1.0
Date: 2010-5-20
Author: James Kaklamanos <james.kaklamanos@tufts.edu> and Eric M.
Thompson <eric.thompson@tufts.edu>
Maintainer: James Kaklamanos <james.kaklamanos@tufts.edu>
License: GPL-2
Packaged: 2010-05-20 19:52:04 UTC; jkakla01
Repository: CRAN
Date/Publication: 2010-05-22 05:23:36