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DDPstar  

Density Regression via Dirichlet Process Mixtures of Normal Structured Additive Regression Models
View on CRAN: Click here


Download and install DDPstar package within the R console
Install from CRAN:
install.packages("DDPstar")

Install from Github:
library("remotes")
install_github("cran/DDPstar")

Install by package version:
library("remotes")
install_version("DDPstar", "1.0-1")



Attach the package and use:
library("DDPstar")
Maintained by
Maria Xose Rodriguez-Alvarez
[Scholar Profile | Author Map]
First Published: 2025-01-31
Latest Update: 2025-01-31
Description:
Implements a flexible, versatile, and computationally tractable model for density regression based on a single-weights dependent Dirichlet process mixture of normal distributions model for univariate continuous responses. The model assumes an additive structure for the mean of each mixture component and the effects of continuous covariates are captured through smooth nonlinear functions. The key components of our modelling approach are penalised B-splines and their bivariate tensor product extension. The proposed method can also easily deal with parametric effects of categorical covariates, linear effects of continuous covariates, interactions between categorical and/or continuous covariates, varying coefficient terms, and random effects. Please see Rodriguez-Alvarez, Inacio et al. (2025) for more details.
How to cite:
Maria Xose Rodriguez-Alvarez (2025). DDPstar: Density Regression via Dirichlet Process Mixtures of Normal Structured Additive Regression Models. R package version 1.0-1, https://cran.r-project.org/web/packages/DDPstar. Accessed 03 May. 2025.
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