DPpackage

Bayesian Nonparametric Modeling in R

Functions to perform inference via simulation from the posterior distributions for Bayesian nonparametric and semiparametric models. Although the name of the package was motivated by the Dirichlet Process prior, the package considers and will consider other priors on functional spaces. So far, DPpackage includes models considering Dirichlet Processes, Dependent Dirichlet Processes, Dependent Poisson- Dirichlet Processes, Hierarchical Dirichlet Processes, Polya Trees, Linear Dependent Tailfree Processes, Mixtures of Triangular distributions, Random Bernstein polynomials priors and Dependent Bernstein Polynomials. The package also includes models considering Penalized B-Splines. Includes semiparametric models for marginal and conditional density estimation, ROC curve analysis, interval censored data, binary regression models, generalized linear mixed models, IRT type models, and generalized additive models. Also contains functions to compute Pseudo-Bayes factors for model comparison, and to elicitate the precision parameter of the Dirichlet Process. To maximize computational efficiency, the actual sampling for each model is done in compiled FORTRAN. The functions return objects which can be subsequently analyzed with functions provided in the 'coda' package.

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Description file content

Package
DPpackage
Version
1.1-7.1
Date
2017-12-05
Title
Bayesian Nonparametric Modeling in R
Depends
R (>= 2.10)
Imports
MASS, nlme, survival, splines, methods
Description
Functions to perform inference via simulation from the posterior distributions for Bayesian nonparametric and semiparametric models. Although the name of the package was motivated by the Dirichlet Process prior, the package considers and will consider other priors on functional spaces. So far, DPpackage includes models considering Dirichlet Processes, Dependent Dirichlet Processes, Dependent Poisson- Dirichlet Processes, Hierarchical Dirichlet Processes, Polya Trees, Linear Dependent Tailfree Processes, Mixtures of Triangular distributions, Random Bernstein polynomials priors and Dependent Bernstein Polynomials. The package also includes models considering Penalized B-Splines. Includes semiparametric models for marginal and conditional density estimation, ROC curve analysis, interval censored data, binary regression models, generalized linear mixed models, IRT type models, and generalized additive models. Also contains functions to compute Pseudo-Bayes factors for model comparison, and to elicitate the precision parameter of the Dirichlet Process. To maximize computational efficiency, the actual sampling for each model is done in compiled FORTRAN. The functions return objects which can be subsequently analyzed with functions provided in the 'coda' package.
License
GPL (>= 2)
URL
Author
Alejandro Jara [aut, cre], Timothy Hanson [ctb], Fernando Quintana [ctb], Peter Mueller [ctb], Gary Rosner [ctb]
Maintainer
ORPHANED
NeedsCompilation
yes
Packaged
2017-12-05 11:35:57 UTC; ripley
X-CRAN-Original-Maintainer
Alejandro Jara
X-CRAN-Comment
Orphaned and corrected on 2017-09-15 as errors were not corrected despite repeated reminders.
Repository
CRAN
Date/Publication
2017-12-05 11:54:46 UTC

install.packages('DPpackage')

1.1-7.1

8 days ago

http://www.mat.puc.cl/~ajara

ORPHANED

GPL (>= 2)

Depends on

R (>= 2.10)

Imports

MASS, nlme, survival, splines, methods

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