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RcppDPR (version 0.1.10)

'Rcpp' Implementation of Dirichlet Process Regression

Description

'Rcpp' reimplementation of the the Bayesian non-parametric Dirichlet Process Regression model for penalized regression first published in Zeng and Zhou (2017) . A full Bayesian version is implemented with Gibbs sampling, as well as a faster but less accurate variational Bayes approximation.

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Version

Install

install.packages('RcppDPR')

Monthly Downloads

140

Version

0.1.10

License

GPL-3

Maintainer

Mohammad Abu Gazala

Last Published

March 19th, 2025

Functions in RcppDPR (0.1.10)

fit_model

Fit Dirichlet Process Regression model
predict.DPR_Model

Use a DPR model to predict results from new data